From f312a5335558b9ec55f64b827998ec7b4f4b383c Mon Sep 17 00:00:00 2001 From: Tony Date: Sun, 1 Mar 2020 13:32:16 -0600 Subject: [PATCH] Revert "Removed broken video link." This reverts commit eddd1d557939d4ba7dd3e88c856e7953f427067d. --- README.md | 2375 ++++++++++++++++++++++++++--------------------------- 1 file changed, 1152 insertions(+), 1223 deletions(-) diff --git a/README.md b/README.md index be2fc2c..481d56a 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ > The items listed here will prepare you well for a technical interview at just about any software company, > including the giants: Amazon, Facebook, Google, and Microsoft. > -> _Best of luck to you!_ +> *Best of luck to you!*
Translations: @@ -78,49 +78,49 @@ If you want to be a reliability engineer or operations engineer, study more from - [The Daily Plan](#the-daily-plan) - [Algorithmic complexity / Big-O / Asymptotic analysis](#algorithmic-complexity--big-o--asymptotic-analysis) - [Data Structures](#data-structures) - - [Arrays](#arrays) - - [Linked Lists](#linked-lists) - - [Stack](#stack) - - [Queue](#queue) - - [Hash table](#hash-table) + - [Arrays](#arrays) + - [Linked Lists](#linked-lists) + - [Stack](#stack) + - [Queue](#queue) + - [Hash table](#hash-table) - [More Knowledge](#more-knowledge) - - [Binary search](#binary-search) - - [Bitwise operations](#bitwise-operations) + - [Binary search](#binary-search) + - [Bitwise operations](#bitwise-operations) - [Trees](#trees) - - [Trees - Notes & Background](#trees---notes--background) - - [Binary search trees: BSTs](#binary-search-trees-bsts) - - [Heap / Priority Queue / Binary Heap](#heap--priority-queue--binary-heap) - - balanced search trees (general concept, not details) - - traversals: preorder, inorder, postorder, BFS, DFS + - [Trees - Notes & Background](#trees---notes--background) + - [Binary search trees: BSTs](#binary-search-trees-bsts) + - [Heap / Priority Queue / Binary Heap](#heap--priority-queue--binary-heap) + - balanced search trees (general concept, not details) + - traversals: preorder, inorder, postorder, BFS, DFS - [Sorting](#sorting) - - selection - - insertion - - heapsort - - quicksort - - merge sort + - selection + - insertion + - heapsort + - quicksort + - merge sort - [Graphs](#graphs) - - directed - - undirected - - adjacency matrix - - adjacency list - - traversals: BFS, DFS + - directed + - undirected + - adjacency matrix + - adjacency list + - traversals: BFS, DFS - [Even More Knowledge](#even-more-knowledge) - - [Recursion](#recursion) - - [Dynamic Programming](#dynamic-programming) - - [Object-Oriented Programming](#object-oriented-programming) - - [Design Patterns](#design-patterns) - - [Combinatorics (n choose k) & Probability](#combinatorics-n-choose-k--probability) - - [NP, NP-Complete and Approximation Algorithms](#np-np-complete-and-approximation-algorithms) - - [Caches](#caches) - - [Processes and Threads](#processes-and-threads) - - [Testing](#testing) - - [Scheduling](#scheduling) - - [String searching & manipulations](#string-searching--manipulations) - - [Tries](#tries) - - [Floating Point Numbers](#floating-point-numbers) - - [Unicode](#unicode) - - [Endianness](#endianness) - - [Networking](#networking) + - [Recursion](#recursion) + - [Dynamic Programming](#dynamic-programming) + - [Object-Oriented Programming](#object-oriented-programming) + - [Design Patterns](#design-patterns) + - [Combinatorics (n choose k) & Probability](#combinatorics-n-choose-k--probability) + - [NP, NP-Complete and Approximation Algorithms](#np-np-complete-and-approximation-algorithms) + - [Caches](#caches) + - [Processes and Threads](#processes-and-threads) + - [Testing](#testing) + - [Scheduling](#scheduling) + - [String searching & manipulations](#string-searching--manipulations) + - [Tries](#tries) + - [Floating Point Numbers](#floating-point-numbers) + - [Unicode](#unicode) + - [Endianness](#endianness) + - [Networking](#networking) - [System Design, Scalability, Data Handling](#system-design-scalability-data-handling) (if you have 4+ years experience) - [Final Review](#final-review) - [Coding Question Practice](#coding-question-practice) @@ -137,43 +137,43 @@ If you want to be a reliability engineer or operations engineer, study more from - [Additional Books](#additional-books) - [Additional Learning](#additional-learning) - - [Compilers](#compilers) - - [Emacs and vi(m)](#emacs-and-vim) - - [Unix command line tools](#unix-command-line-tools) - - [Information theory](#information-theory-videos) - - [Parity & Hamming Code](#parity--hamming-code-videos) - - [Entropy](#entropy) - - [Cryptography](#cryptography) - - [Compression](#compression) - - [Computer Security](#computer-security) - - [Garbage collection](#garbage-collection) - - [Parallel Programming](#parallel-programming) - - [Messaging, Serialization, and Queueing Systems](#messaging-serialization-and-queueing-systems) - - [A\*](#a) - - [Fast Fourier Transform](#fast-fourier-transform) - - [Bloom Filter](#bloom-filter) - - [HyperLogLog](#hyperloglog) - - [Locality-Sensitive Hashing](#locality-sensitive-hashing) - - [van Emde Boas Trees](#van-emde-boas-trees) - - [Augmented Data Structures](#augmented-data-structures) - - [Balanced search trees](#balanced-search-trees) - - AVL trees - - Splay trees - - Red/black trees - - 2-3 search trees - - 2-3-4 Trees (aka 2-4 trees) - - N-ary (K-ary, M-ary) trees - - B-Trees - - [k-D Trees](#k-d-trees) - - [Skip lists](#skip-lists) - - [Network Flows](#network-flows) - - [Disjoint Sets & Union Find](#disjoint-sets--union-find) - - [Math for Fast Processing](#math-for-fast-processing) - - [Treap](#treap) - - [Linear Programming](#linear-programming-videos) - - [Geometry, Convex hull](#geometry-convex-hull-videos) - - [Discrete math](#discrete-math) - - [Machine Learning](#machine-learning) + - [Compilers](#compilers) + - [Emacs and vi(m)](#emacs-and-vim) + - [Unix command line tools](#unix-command-line-tools) + - [Information theory](#information-theory-videos) + - [Parity & Hamming Code](#parity--hamming-code-videos) + - [Entropy](#entropy) + - [Cryptography](#cryptography) + - [Compression](#compression) + - [Computer Security](#computer-security) + - [Garbage collection](#garbage-collection) + - [Parallel Programming](#parallel-programming) + - [Messaging, Serialization, and Queueing Systems](#messaging-serialization-and-queueing-systems) + - [A*](#a) + - [Fast Fourier Transform](#fast-fourier-transform) + - [Bloom Filter](#bloom-filter) + - [HyperLogLog](#hyperloglog) + - [Locality-Sensitive Hashing](#locality-sensitive-hashing) + - [van Emde Boas Trees](#van-emde-boas-trees) + - [Augmented Data Structures](#augmented-data-structures) + - [Balanced search trees](#balanced-search-trees) + - AVL trees + - Splay trees + - Red/black trees + - 2-3 search trees + - 2-3-4 Trees (aka 2-4 trees) + - N-ary (K-ary, M-ary) trees + - B-Trees + - [k-D Trees](#k-d-trees) + - [Skip lists](#skip-lists) + - [Network Flows](#network-flows) + - [Disjoint Sets & Union Find](#disjoint-sets--union-find) + - [Math for Fast Processing](#math-for-fast-processing) + - [Treap](#treap) + - [Linear Programming](#linear-programming-videos) + - [Geometry, Convex hull](#geometry-convex-hull-videos) + - [Discrete math](#discrete-math) + - [Machine Learning](#machine-learning) - [Additional Detail on Some Subjects](#additional-detail-on-some-subjects) - [Video Series](#video-series) - [Computer Science Courses](#computer-science-courses) @@ -200,6 +200,7 @@ I'm using Github's special markdown flavor, including tasks lists to check progr **Create a new branch so you can check items like this, just put an x in the brackets: [x]** + Fork a branch and follow the commands below `git checkout -b progress` @@ -220,6 +221,7 @@ I'm using Github's special markdown flavor, including tasks lists to check progr [More about Github-flavored markdown](https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown) + ## Don't feel you aren't smart enough - Successful software engineers are smart, but many have an insecurity that they aren't smart enough. @@ -234,6 +236,7 @@ Sometimes the classes are not in session so you have to wait a couple of months, I'd appreciate your help to add free and always-available public sources, such as YouTube videos to accompany the online course videos. I like using university lectures. + ## Interview Process & General Interview Prep - [ ] [ABC: Always Be Coding](https://medium.com/always-be-coding/abc-always-be-coding-d5f8051afce2#.4heg8zvm4) @@ -241,22 +244,22 @@ Sometimes the classes are not in session so you have to wait a couple of months, - [ ] [Effective Whiteboarding during Programming Interviews](http://www.coderust.com/blog/2014/04/10/effective-whiteboarding-during-programming-interviews/) - [ ] [Demystifying Tech Recruiting](https://www.youtube.com/watch?v=N233T0epWTs) - [ ] How to Get a Job at the Big 4: - - [ ] [How to Get a Job at the Big 4 - Amazon, Facebook, Google & Microsoft (video)](https://www.youtube.com/watch?v=YJZCUhxNCv8) + - [ ] [How to Get a Job at the Big 4 - Amazon, Facebook, Google & Microsoft (video)](https://www.youtube.com/watch?v=YJZCUhxNCv8) - [ ] Cracking The Coding Interview Set 1: - - [ ] [Gayle L McDowell - Cracking The Coding Interview (video)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ) - - [ ] [Cracking the Coding Interview with Author Gayle Laakmann McDowell (video)](https://www.youtube.com/watch?v=aClxtDcdpsQ) + - [ ] [Gayle L McDowell - Cracking The Coding Interview (video)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ) + - [ ] [Cracking the Coding Interview with Author Gayle Laakmann McDowell (video)](https://www.youtube.com/watch?v=aClxtDcdpsQ) - [ ] Cracking the Facebook Coding Interview - - [ ] [The Approach](https://www.youtube.com/watch?v=wCl9kvQGHPI) - - [ ] [Problem Walkthrough](https://www.youtube.com/watch?v=4UWDyJq8jZg) + - [ ] [The Approach](https://www.youtube.com/watch?v=wCl9kvQGHPI) + - [ ] [Problem Walkthrough](https://www.youtube.com/watch?v=4UWDyJq8jZg) - [ ] Prep Course: - - [ ] [Software Engineer Interview Unleashed (paid course)](https://www.udemy.com/software-engineer-interview-unleashed): - - Learn how to make yourself ready for software engineer interviews from a former Google interviewer. - - [ ] [Python for Data Structures, Algorithms, and Interviews (paid course)](https://www.udemy.com/python-for-data-structures-algorithms-and-interviews/): - - A Python centric interview prep course which covers data structures, algorithms, mock interviews and much more. - - [ ] [Intro to Data Structures and Algorithms using Python (Udacity free course)](https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513): - - A free Python centric data structures and algorithms course. - - [ ] [Data Structures and Algorithms Nanodegree! (Udacity paid Nanodegree)](https://www.udacity.com/course/data-structures-and-algorithms-nanodegree--nd256): - - Get hands-on practice with over 100 data structures and algorithm exercises and guidance from a dedicated mentor to help prepare you for interviews and on-the-job scenarios. + - [ ] [Software Engineer Interview Unleashed (paid course)](https://www.udemy.com/software-engineer-interview-unleashed): + - Learn how to make yourself ready for software engineer interviews from a former Google interviewer. + - [ ] [Python for Data Structures, Algorithms, and Interviews (paid course)](https://www.udemy.com/python-for-data-structures-algorithms-and-interviews/): + - A Python centric interview prep course which covers data structures, algorithms, mock interviews and much more. + - [ ] [Intro to Data Structures and Algorithms using Python (Udacity free course)](https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513): + - A free Python centric data structures and algorithms course. + - [ ] [Data Structures and Algorithms Nanodegree! (Udacity paid Nanodegree)](https://www.udacity.com/course/data-structures-and-algorithms-nanodegree--nd256): + - Get hands-on practice with over 100 data structures and algorithm exercises and guidance from a dedicated mentor to help prepare you for interviews and on-the-job scenarios. ## Pick One Language for the Interview @@ -276,7 +279,6 @@ Here is an article I wrote about choosing a language for the interview: [Pick On You need to be very comfortable in the language and be knowledgeable. Read more about choices: - - http://www.byte-by-byte.com/choose-the-right-language-for-your-coding-interview/ - http://blog.codingforinterviews.com/best-programming-language-jobs/ @@ -291,11 +293,11 @@ This is a shorter list than what I used. This is abbreviated to save you time. ### Interview Prep - [ ] [Programming Interviews Exposed: Coding Your Way Through the Interview, 4th Edition](https://www.amazon.com/Programming-Interviews-Exposed-Through-Interview/dp/111941847X/) - - answers in C++ and Java - - this is a good warm-up for Cracking the Coding Interview - - not too difficult, most problems may be easier than what you'll see in an interview (from what I've read) + - answers in C++ and Java + - this is a good warm-up for Cracking the Coding Interview + - not too difficult, most problems may be easier than what you'll see in an interview (from what I've read) - [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/) - - answers in Java + - answers in Java ### If you have tons of extra time: @@ -304,8 +306,8 @@ Choose one: - [ ] [Elements of Programming Interviews (C++ version)](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836) - [ ] [Elements of Programming Interviews in Python](https://www.amazon.com/Elements-Programming-Interviews-Python-Insiders/dp/1537713949/) - [ ] Elements of Programming Interviews (Java version) - - [book](https://www.amazon.com/Elements-Programming-Interviews-Java-Insiders/dp/1517435803/) - - [Companion Project - Method Stub and Test Cases for Every Problem in the Book](https://github.com/gardncl/elements-of-programming-interviews) + - [book](https://www.amazon.com/Elements-Programming-Interviews-Java-Insiders/dp/1517435803/) + - [Companion Project - Method Stub and Test Cases for Every Problem in the Book](https://github.com/gardncl/elements-of-programming-interviews) ### Language Specific @@ -330,24 +332,25 @@ If you have a better recommendation for C++, please let me know. Looking for a c ### Java - [ ] [Algorithms (Sedgewick and Wayne)](https://www.amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X/) - - videos with book content (and Sedgewick!) on coursera: - - [Algorithms I](https://www.coursera.org/learn/algorithms-part1) - - [Algorithms II](https://www.coursera.org/learn/algorithms-part2) + - videos with book content (and Sedgewick!) on coursera: + - [Algorithms I](https://www.coursera.org/learn/algorithms-part1) + - [Algorithms II](https://www.coursera.org/learn/algorithms-part2) OR: - [ ] [Data Structures and Algorithms in Java](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/1118771338/) - - by Goodrich, Tamassia, Goldwasser - - used as optional text for CS intro course at UC Berkeley - - see my book report on the Python version below. This book covers the same topics. + - by Goodrich, Tamassia, Goldwasser + - used as optional text for CS intro course at UC Berkeley + - see my book report on the Python version below. This book covers the same topics. ### Python - [ ] [Data Structures and Algorithms in Python](https://www.amazon.com/Structures-Algorithms-Python-Michael-Goodrich/dp/1118290275/) - - by Goodrich, Tamassia, Goldwasser - - I loved this book. It covered everything and more. - - Pythonic code - - my glowing book report: https://startupnextdoor.com/book-report-data-structures-and-algorithms-in-python/ + - by Goodrich, Tamassia, Goldwasser + - I loved this book. It covered everything and more. + - Pythonic code + - my glowing book report: https://startupnextdoor.com/book-report-data-structures-and-algorithms-in-python/ + ## Before you Get Started @@ -386,17 +389,17 @@ same card and answer it several times correctly before you really know it. Repet your brain. An alternative to using my flashcard site is [Anki](http://ankisrs.net/), which has been recommended to me numerous times. It uses a repetition system to help you remember. -It's user-friendly, available on all platforms and has a cloud sync system. It costs \$25 on iOS but is free on other platforms. +It's user-friendly, available on all platforms and has a cloud sync system. It costs $25 on iOS but is free on other platforms. My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (thanks [@xiewenya](https://github.com/xiewenya)) -### 3. Start doing coding interview questions while you're learning data structures and algorithms, +### 3. Start doing coding interview questions while you're learning data structures and algorithms, -You need to apply what you're learning to solving problems, or you'll forget. I made this mistake. Once you've learned a topic, -and feel comfortable with it, like linked lists, open one of the coding interview books and do a couple of questions regarding -linked lists. Then move on to the next learning topic. Then later, go back and do another linked list problem, -or recursion problem, or whatever. But keep doing problems while you're learning. You're not being hired for knowledge, -but how you apply the knowledge. There are several books and sites I recommend. +You need to apply what you're learning to solving problems, or you'll forget. I made this mistake. Once you've learned a topic, +and feel comfortable with it, like linked lists, open one of the coding interview books and do a couple of questions regarding +linked lists. Then move on to the next learning topic. Then later, go back and do another linked list problem, +or recursion problem, or whatever. But keep doing problems while you're learning. You're not being hired for knowledge, +but how you apply the knowledge. There are several books and sites I recommend. See here for more: [Coding Question Practice](#coding-question-practice) ### 4. Review, review, review @@ -407,7 +410,7 @@ Take a break from programming problems for a half hour and go through your flash ### 5. Focus -There are a lot of distractions that can take up valuable time. Focus and concentration are hard. Turn on some music +There are a lot of distractions that can take up valuable time. Focus and concentration are hard. Turn on some music without lyrics and you'll be able to focus pretty well. ## What you won't see covered @@ -423,8 +426,7 @@ These are prevalent technologies but not part of this study plan: Some subjects take one day, and some will take multiple days. Some are just learning with nothing to implement. Each day I take one subject from the list below, watch videos about that subject, and write an implementation in: - -- C - using structs and functions that take a struct \* and something else as args. +- C - using structs and functions that take a struct * and something else as args. - C++ - without using built-in types - C++ - using built-in types, like STL's std::list for a linked list - Python - using built-in types (to keep practicing Python) @@ -434,7 +436,6 @@ Each day I take one subject from the list below, watch videos about that subject You don't need all these. You need only [one language for the interview](#pick-one-language-for-the-interview). Why code in all of these? - - Practice, practice, practice, until I'm sick of it, and can do it with no problem (some have many edge cases and bookkeeping details to remember) - Work within the raw constraints (allocating/freeing memory without help of garbage collection (except Python or Java)) - Make use of built-in types so I have experience using the built-in tools for real-world use (not going to write my own linked list implementation in production) @@ -442,10 +443,9 @@ Why code in all of these? I may not have time to do all of these for every subject, but I'll try. You can see my code here: - -- [C](https://github.com/jwasham/practice-c) -- [C++](https://github.com/jwasham/practice-cpp) -- [Python](https://github.com/jwasham/practice-python) + - [C](https://github.com/jwasham/practice-c) + - [C++](https://github.com/jwasham/practice-cpp) + - [Python](https://github.com/jwasham/practice-python) You don't need to memorize the guts of every algorithm. @@ -454,19 +454,18 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input ## Prerequisite Knowledge - [ ] **Learn C** - - - C is everywhere. You'll see examples in books, lectures, videos, _everywhere_ while you're studying. - - [ ] [C Programming Language, Vol 2](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628) - - This is a short book, but it will give you a great handle on the C language and if you practice it a little - you'll quickly get proficient. Understanding C helps you understand how programs and memory work. - - [answers to questions](https://github.com/lekkas/c-algorithms) + - C is everywhere. You'll see examples in books, lectures, videos, *everywhere* while you're studying. + - [ ] [C Programming Language, Vol 2](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628) + - This is a short book, but it will give you a great handle on the C language and if you practice it a little + you'll quickly get proficient. Understanding C helps you understand how programs and memory work. + - [answers to questions](https://github.com/lekkas/c-algorithms) - [ ] **How computers process a program:** - - [ ] [How CPU executes a program (video)](https://www.youtube.com/watch?v=XM4lGflQFvA) - - [ ] [How computers calculate - ALU (video)](https://youtu.be/1I5ZMmrOfnA) - - [ ] [Registers and RAM (video)](https://youtu.be/fpnE6UAfbtU) - - [ ] [The Central Processing Unit (CPU) (video)](https://youtu.be/FZGugFqdr60) - - [ ] [Instructions and Programs (video)](https://youtu.be/zltgXvg6r3k) + - [ ] [How CPU executes a program (video)](https://www.youtube.com/watch?v=XM4lGflQFvA) + - [ ] [How computers calculate - ALU (video)](https://youtu.be/1I5ZMmrOfnA) + - [ ] [Registers and RAM (video)](https://youtu.be/fpnE6UAfbtU) + - [ ] [The Central Processing Unit (CPU) (video)](https://youtu.be/FZGugFqdr60) + - [ ] [Instructions and Programs (video)](https://youtu.be/zltgXvg6r3k) ## Algorithmic complexity / Big-O / Asymptotic analysis @@ -477,8 +476,8 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - [ ] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU) - [ ] [Big O Notation (and Omega and Theta) - best mathematical explanation (video)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN) - [ ] Skiena: - - [video](https://www.youtube.com/watch?v=gSyDMtdPNpU&index=2&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [slides](http://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture2.pdf) + - [video](https://www.youtube.com/watch?v=gSyDMtdPNpU&index=2&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [slides](http://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture2.pdf) - [ ] [A Gentle Introduction to Algorithm Complexity Analysis](http://discrete.gr/complexity/) - [ ] [Orders of Growth (video)](https://www.coursera.org/lecture/algorithmic-thinking-1/orders-of-growth-6PKkX) - [ ] [Asymptotics (video)](https://www.coursera.org/lecture/algorithmic-thinking-1/asymptotics-bXAtM) @@ -487,300 +486,287 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - [ ] [Amortized Analysis (video)](https://www.youtube.com/watch?v=B3SpQZaAZP4&index=10&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN) - [ ] [Illustrating "Big O" (video)](https://www.coursera.org/lecture/algorithmic-thinking-1/illustrating-big-o-YVqzv) - [ ] TopCoder (includes recurrence relations and master theorem): - - [Computational Complexity: Section 1](https://www.topcoder.com/community/competitive-programming/tutorials/computational-complexity-section-1/) - - [Computational Complexity: Section 2](https://www.topcoder.com/community/competitive-programming/tutorials/computational-complexity-section-2/) + - [Computational Complexity: Section 1](https://www.topcoder.com/community/competitive-programming/tutorials/computational-complexity-section-1/) + - [Computational Complexity: Section 2](https://www.topcoder.com/community/competitive-programming/tutorials/computational-complexity-section-2/) - [ ] [Cheat sheet](http://bigocheatsheet.com/) ## Data Structures - ### Arrays - - - Implement an automatically resizing vector. - - [ ] Description: - - [Arrays (video)](https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays) - - [UC Berkeley CS61B - Linear and Multi-Dim Arrays (video)](https://archive.org/details/ucberkeley_webcast_Wp8oiO_CZZE) (Start watching from 15m 32s) - - [Basic Arrays (video)](https://archive.org/details/0102WhatYouShouldKnow/02_04-basicArrays.mp4) - - [Multi-dim (video)](https://archive.org/details/0102WhatYouShouldKnow/02_05-multidimensionalArrays.mp4) - - [Dynamic Arrays (video)](https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays) - - [Jagged Arrays (video)](https://www.youtube.com/watch?v=1jtrQqYpt7g) - - [Jagged Arrays (video)](https://archive.org/details/0102WhatYouShouldKnow/02_06-jaggedArrays.mp4) - - [Resizing arrays (video)](https://archive.org/details/0102WhatYouShouldKnow/03_01-resizableArrays.mp4) - - [ ] Implement a vector (mutable array with automatic resizing): - - [ ] Practice coding using arrays and pointers, and pointer math to jump to an index instead of using indexing. - - [ ] new raw data array with allocated memory - - can allocate int array under the hood, just not use its features - - start with 16, or if starting number is greater, use power of 2 - 16, 32, 64, 128 - - [ ] size() - number of items - - [ ] capacity() - number of items it can hold - - [ ] is_empty() - - [ ] at(index) - returns item at given index, blows up if index out of bounds - - [ ] push(item) - - [ ] insert(index, item) - inserts item at index, shifts that index's value and trailing elements to the right - - [ ] prepend(item) - can use insert above at index 0 - - [ ] pop() - remove from end, return value - - [ ] delete(index) - delete item at index, shifting all trailing elements left - - [ ] remove(item) - looks for value and removes index holding it (even if in multiple places) - - [ ] find(item) - looks for value and returns first index with that value, -1 if not found - - [ ] resize(new_capacity) // private function - - when you reach capacity, resize to double the size - - when popping an item, if size is 1/4 of capacity, resize to half - - [ ] Time - - O(1) to add/remove at end (amortized for allocations for more space), index, or update - - O(n) to insert/remove elsewhere - - [ ] Space - - contiguous in memory, so proximity helps performance - - space needed = (array capacity, which is >= n) \* size of item, but even if 2n, still O(n) + - Implement an automatically resizing vector. + - [ ] Description: + - [Arrays (video)](https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays) + - [UC Berkeley CS61B - Linear and Multi-Dim Arrays (video)](https://archive.org/details/ucberkeley_webcast_Wp8oiO_CZZE) (Start watching from 15m 32s) + - [Basic Arrays (video)](https://archive.org/details/0102WhatYouShouldKnow/02_04-basicArrays.mp4) + - [Multi-dim (video)](https://archive.org/details/0102WhatYouShouldKnow/02_05-multidimensionalArrays.mp4) + - [Dynamic Arrays (video)](https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays) + - [Jagged Arrays (video)](https://www.youtube.com/watch?v=1jtrQqYpt7g) + - [Jagged Arrays (video)](https://archive.org/details/0102WhatYouShouldKnow/02_06-jaggedArrays.mp4) + - [Resizing arrays (video)](https://archive.org/details/0102WhatYouShouldKnow/03_01-resizableArrays.mp4) + - [ ] Implement a vector (mutable array with automatic resizing): + - [ ] Practice coding using arrays and pointers, and pointer math to jump to an index instead of using indexing. + - [ ] new raw data array with allocated memory + - can allocate int array under the hood, just not use its features + - start with 16, or if starting number is greater, use power of 2 - 16, 32, 64, 128 + - [ ] size() - number of items + - [ ] capacity() - number of items it can hold + - [ ] is_empty() + - [ ] at(index) - returns item at given index, blows up if index out of bounds + - [ ] push(item) + - [ ] insert(index, item) - inserts item at index, shifts that index's value and trailing elements to the right + - [ ] prepend(item) - can use insert above at index 0 + - [ ] pop() - remove from end, return value + - [ ] delete(index) - delete item at index, shifting all trailing elements left + - [ ] remove(item) - looks for value and removes index holding it (even if in multiple places) + - [ ] find(item) - looks for value and returns first index with that value, -1 if not found + - [ ] resize(new_capacity) // private function + - when you reach capacity, resize to double the size + - when popping an item, if size is 1/4 of capacity, resize to half + - [ ] Time + - O(1) to add/remove at end (amortized for allocations for more space), index, or update + - O(n) to insert/remove elsewhere + - [ ] Space + - contiguous in memory, so proximity helps performance + - space needed = (array capacity, which is >= n) * size of item, but even if 2n, still O(n) - ### Linked Lists - - - [ ] Description: - - [ ] [Singly Linked Lists (video)](https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists) - - [ ] [CS 61B - Linked Lists 1 (video)](https://archive.org/details/ucberkeley_webcast_htzJdKoEmO0) - - [ ] [CS 61B - Linked Lists 2 (video)](https://archive.org/details/ucberkeley_webcast_-c4I3gFYe3w) - - [ ] [C Code (video)](https://www.youtube.com/watch?v=QN6FPiD0Gzo) - not the whole video, just portions about Node struct and memory allocation. - - [ ] Linked List vs Arrays: - - [Core Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays) - - [In The Real World Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/QUaUd/in-the-real-world-lists-vs-arrays) - - [ ] [why you should avoid linked lists (video)](https://www.youtube.com/watch?v=YQs6IC-vgmo) - - [ ] Gotcha: you need pointer to pointer knowledge: + - [ ] Description: + - [ ] [Singly Linked Lists (video)](https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists) + - [ ] [CS 61B - Linked Lists 1 (video)](https://archive.org/details/ucberkeley_webcast_htzJdKoEmO0) + - [ ] [CS 61B - Linked Lists 2 (video)](https://archive.org/details/ucberkeley_webcast_-c4I3gFYe3w) + - [ ] [C Code (video)](https://www.youtube.com/watch?v=QN6FPiD0Gzo) + - not the whole video, just portions about Node struct and memory allocation. + - [ ] Linked List vs Arrays: + - [Core Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays) + - [In The Real World Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/QUaUd/in-the-real-world-lists-vs-arrays) + - [ ] [why you should avoid linked lists (video)](https://www.youtube.com/watch?v=YQs6IC-vgmo) + - [ ] Gotcha: you need pointer to pointer knowledge: (for when you pass a pointer to a function that may change the address where that pointer points) This page is just to get a grasp on ptr to ptr. I don't recommend this list traversal style. Readability and maintainability suffer due to cleverness. - - [Pointers to Pointers](https://www.eskimo.com/~scs/cclass/int/sx8.html) - - [ ] implement (I did with tail pointer & without): - - [ ] size() - returns number of data elements in list - - [ ] empty() - bool returns true if empty - - [ ] value_at(index) - returns the value of the nth item (starting at 0 for first) - - [ ] push_front(value) - adds an item to the front of the list - - [ ] pop_front() - remove front item and return its value - - [ ] push_back(value) - adds an item at the end - - [ ] pop_back() - removes end item and returns its value - - [ ] front() - get value of front item - - [ ] back() - get value of end item - - [ ] insert(index, value) - insert value at index, so current item at that index is pointed to by new item at index - - [ ] erase(index) - removes node at given index - - [ ] value_n_from_end(n) - returns the value of the node at nth position from the end of the list - - [ ] reverse() - reverses the list - - [ ] remove_value(value) - removes the first item in the list with this value - - [ ] Doubly-linked List - - [Description (video)](https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists) - - No need to implement + - [Pointers to Pointers](https://www.eskimo.com/~scs/cclass/int/sx8.html) + - [ ] implement (I did with tail pointer & without): + - [ ] size() - returns number of data elements in list + - [ ] empty() - bool returns true if empty + - [ ] value_at(index) - returns the value of the nth item (starting at 0 for first) + - [ ] push_front(value) - adds an item to the front of the list + - [ ] pop_front() - remove front item and return its value + - [ ] push_back(value) - adds an item at the end + - [ ] pop_back() - removes end item and returns its value + - [ ] front() - get value of front item + - [ ] back() - get value of end item + - [ ] insert(index, value) - insert value at index, so current item at that index is pointed to by new item at index + - [ ] erase(index) - removes node at given index + - [ ] value_n_from_end(n) - returns the value of the node at nth position from the end of the list + - [ ] reverse() - reverses the list + - [ ] remove_value(value) - removes the first item in the list with this value + - [ ] Doubly-linked List + - [Description (video)](https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists) + - No need to implement - ### Stack - - - [ ] [Stacks (video)](https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks) - - [ ] [Using Stacks Last-In First-Out (video)](https://archive.org/details/0102WhatYouShouldKnow/05_01-usingStacksForLast-inFirst-out.mp4) - - [ ] Will not implement. Implementing with array is trivial. + - [ ] [Stacks (video)](https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks) + - [ ] [Using Stacks Last-In First-Out (video)](https://archive.org/details/0102WhatYouShouldKnow/05_01-usingStacksForLast-inFirst-out.mp4) + - [ ] Will not implement. Implementing with array is trivial. - ### Queue - - - [ ] [Using Queues First-In First-Out(video)](https://archive.org/details/0102WhatYouShouldKnow/05_03-usingQueuesForFirst-inFirst-out.mp4) - - [ ] [Queue (video)](https://www.coursera.org/lecture/data-structures/queues-EShpq) - - [ ] [Circular buffer/FIFO](https://en.wikipedia.org/wiki/Circular_buffer) - - [ ] [Priority Queues (video)](https://archive.org/details/0102WhatYouShouldKnow/05_04-priorityQueuesAndDeques.mp4) - - [ ] Implement using linked-list, with tail pointer: - - enqueue(value) - adds value at position at tail - - dequeue() - returns value and removes least recently added element (front) - - empty() - - [ ] Implement using fixed-sized array: - - enqueue(value) - adds item at end of available storage - - dequeue() - returns value and removes least recently added element - - empty() - - full() - - [ ] Cost: - - a bad implementation using linked list where you enqueue at head and dequeue at tail would be O(n) - because you'd need the next to last element, causing a full traversal each dequeue - - enqueue: O(1) (amortized, linked list and array [probing]) - - dequeue: O(1) (linked list and array) - - empty: O(1) (linked list and array) + - [ ] [Using Queues First-In First-Out(video)](https://archive.org/details/0102WhatYouShouldKnow/05_03-usingQueuesForFirst-inFirst-out.mp4) + - [ ] [Queue (video)](https://www.coursera.org/lecture/data-structures/queues-EShpq) + - [ ] [Circular buffer/FIFO](https://en.wikipedia.org/wiki/Circular_buffer) + - [ ] [Priority Queues (video)](https://archive.org/details/0102WhatYouShouldKnow/05_04-priorityQueuesAndDeques.mp4) + - [ ] Implement using linked-list, with tail pointer: + - enqueue(value) - adds value at position at tail + - dequeue() - returns value and removes least recently added element (front) + - empty() + - [ ] Implement using fixed-sized array: + - enqueue(value) - adds item at end of available storage + - dequeue() - returns value and removes least recently added element + - empty() + - full() + - [ ] Cost: + - a bad implementation using linked list where you enqueue at head and dequeue at tail would be O(n) + because you'd need the next to last element, causing a full traversal each dequeue + - enqueue: O(1) (amortized, linked list and array [probing]) + - dequeue: O(1) (linked list and array) + - empty: O(1) (linked list and array) - ### Hash table + - [ ] Videos: + - [ ] [Hashing with Chaining (video)](https://www.youtube.com/watch?v=0M_kIqhwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8) + - [ ] [Table Doubling, Karp-Rabin (video)](https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) + - [ ] [Open Addressing, Cryptographic Hashing (video)](https://www.youtube.com/watch?v=rvdJDijO2Ro&index=10&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) + - [ ] [PyCon 2010: The Mighty Dictionary (video)](https://www.youtube.com/watch?v=C4Kc8xzcA68) + - [ ] [(Advanced) Randomization: Universal & Perfect Hashing (video)](https://www.youtube.com/watch?v=z0lJ2k0sl1g&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=11) + - [ ] [(Advanced) Perfect hashing (video)](https://www.youtube.com/watch?v=N0COwN14gt0&list=PL2B4EEwhKD-NbwZ4ezj7gyc_3yNrojKM9&index=4) - - [ ] Videos: + - [ ] Online Courses: + - [ ] [Understanding Hash Functions (video)](https://archive.org/details/0102WhatYouShouldKnow/06_02-understandingHashFunctions.mp4) + - [ ] [Using Hash Tables (video)](https://archive.org/details/0102WhatYouShouldKnow/06_03-usingHashTables.mp4) + - [ ] [Supporting Hashing (video)](https://archive.org/details/0102WhatYouShouldKnow/06_04-supportingHashing.mp4) + - [ ] [Language Support Hash Tables (video)](https://archive.org/details/0102WhatYouShouldKnow/06_05-languageSupportForHashTables.mp4) + - [ ] [Core Hash Tables (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables) + - [ ] [Data Structures (video)](https://www.coursera.org/learn/data-structures/home/week/3) + - [ ] [Phone Book Problem (video)](https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem) + - [ ] distributed hash tables: + - [Instant Uploads And Storage Optimization In Dropbox (video)](https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox) + - [Distributed Hash Tables (video)](https://www.coursera.org/learn/data-structures/lecture/tvH8H/distributed-hash-tables) - - [ ] [Hashing with Chaining (video)](https://www.youtube.com/watch?v=0M_kIqhwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8) - - [ ] [Table Doubling, Karp-Rabin (video)](https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [ ] [Open Addressing, Cryptographic Hashing (video)](https://www.youtube.com/watch?v=rvdJDijO2Ro&index=10&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [ ] [PyCon 2010: The Mighty Dictionary (video)](https://www.youtube.com/watch?v=C4Kc8xzcA68) - - [ ] [(Advanced) Randomization: Universal & Perfect Hashing (video)](https://www.youtube.com/watch?v=z0lJ2k0sl1g&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=11) - - [ ] [(Advanced) Perfect hashing (video)](https://www.youtube.com/watch?v=N0COwN14gt0&list=PL2B4EEwhKD-NbwZ4ezj7gyc_3yNrojKM9&index=4) - - - [ ] Online Courses: - - - [ ] [Understanding Hash Functions (video)](https://archive.org/details/0102WhatYouShouldKnow/06_02-understandingHashFunctions.mp4) - - [ ] [Using Hash Tables (video)](https://archive.org/details/0102WhatYouShouldKnow/06_03-usingHashTables.mp4) - - [ ] [Supporting Hashing (video)](https://archive.org/details/0102WhatYouShouldKnow/06_04-supportingHashing.mp4) - - [ ] [Language Support Hash Tables (video)](https://archive.org/details/0102WhatYouShouldKnow/06_05-languageSupportForHashTables.mp4) - - [ ] [Core Hash Tables (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables) - - [ ] [Data Structures (video)](https://www.coursera.org/learn/data-structures/home/week/3) - - [ ] [Phone Book Problem (video)](https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem) - - [ ] distributed hash tables: - - [Instant Uploads And Storage Optimization In Dropbox (video)](https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox) - - [Distributed Hash Tables (video)](https://www.coursera.org/learn/data-structures/lecture/tvH8H/distributed-hash-tables) - - - [ ] implement with array using linear probing - - hash(k, m) - m is size of hash table - - add(key, value) - if key already exists, update value - - exists(key) - - get(key) - - remove(key) + - [ ] implement with array using linear probing + - hash(k, m) - m is size of hash table + - add(key, value) - if key already exists, update value + - exists(key) + - get(key) + - remove(key) ## More Knowledge - ### Binary search - - - [ ] [Binary Search (video)](https://www.youtube.com/watch?v=D5SrAga1pno) - - [ ] [Binary Search (video)](https://www.khanacademy.org/computing/computer-science/algorithms/binary-search/a/binary-search) - - [ ] [detail](https://www.topcoder.com/community/competitive-programming/tutorials/binary-search/) - - [ ] Implement: - - binary search (on sorted array of integers) - - binary search using recursion + - [ ] [Binary Search (video)](https://www.youtube.com/watch?v=D5SrAga1pno) + - [ ] [Binary Search (video)](https://www.khanacademy.org/computing/computer-science/algorithms/binary-search/a/binary-search) + - [ ] [detail](https://www.topcoder.com/community/competitive-programming/tutorials/binary-search/) + - [ ] Implement: + - binary search (on sorted array of integers) + - binary search using recursion - ### Bitwise operations - - [ ] [Bits cheat sheet](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/bits-cheat-cheet.pdf) - you should know many of the powers of 2 from (2^1 to 2^16 and 2^32) - - [ ] Get a really good understanding of manipulating bits with: &, |, ^, ~, >>, << - - [ ] [words]() - - [ ] Good intro: - [Bit Manipulation (video)](https://www.youtube.com/watch?v=7jkIUgLC29I) - - [ ] [C Programming Tutorial 2-10: Bitwise Operators (video)](https://www.youtube.com/watch?v=d0AwjSpNXR0) - - [ ] [Bit Manipulation](https://en.wikipedia.org/wiki/Bit_manipulation) - - [ ] [Bitwise Operation](https://en.wikipedia.org/wiki/Bitwise_operation) - - [ ] [Bithacks](https://graphics.stanford.edu/~seander/bithacks.html) - - [ ] [The Bit Twiddler](https://bits.stephan-brumme.com/) - - [ ] [The Bit Twiddler Interactive](https://bits.stephan-brumme.com/interactive.html) - - [ ] 2s and 1s complement - - [Binary: Plusses & Minuses (Why We Use Two's Complement) (video)](https://www.youtube.com/watch?v=lKTsv6iVxV4) - - [1s Complement](https://en.wikipedia.org/wiki/Ones%27_complement) - - [2s Complement](https://en.wikipedia.org/wiki/Two%27s_complement) - - [ ] count set bits - - [4 ways to count bits in a byte (video)](https://youtu.be/Hzuzo9NJrlc) - - [Count Bits](https://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetKernighan) - - [How To Count The Number Of Set Bits In a 32 Bit Integer](http://stackoverflow.com/questions/109023/how-to-count-the-number-of-set-bits-in-a-32-bit-integer) - - [ ] swap values: - - [Swap](https://bits.stephan-brumme.com/swap.html) - - [ ] absolute value: - - [Absolute Integer](https://bits.stephan-brumme.com/absInteger.html) + - [ ] [Bits cheat sheet](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/bits-cheat-cheet.pdf) - you should know many of the powers of 2 from (2^1 to 2^16 and 2^32) + - [ ] Get a really good understanding of manipulating bits with: &, |, ^, ~, >>, << + - [ ] [words](https://en.wikipedia.org/wiki/Word_(computer_architecture)) + - [ ] Good intro: + [Bit Manipulation (video)](https://www.youtube.com/watch?v=7jkIUgLC29I) + - [ ] [C Programming Tutorial 2-10: Bitwise Operators (video)](https://www.youtube.com/watch?v=d0AwjSpNXR0) + - [ ] [Bit Manipulation](https://en.wikipedia.org/wiki/Bit_manipulation) + - [ ] [Bitwise Operation](https://en.wikipedia.org/wiki/Bitwise_operation) + - [ ] [Bithacks](https://graphics.stanford.edu/~seander/bithacks.html) + - [ ] [The Bit Twiddler](https://bits.stephan-brumme.com/) + - [ ] [The Bit Twiddler Interactive](https://bits.stephan-brumme.com/interactive.html) + - [ ] 2s and 1s complement + - [Binary: Plusses & Minuses (Why We Use Two's Complement) (video)](https://www.youtube.com/watch?v=lKTsv6iVxV4) + - [1s Complement](https://en.wikipedia.org/wiki/Ones%27_complement) + - [2s Complement](https://en.wikipedia.org/wiki/Two%27s_complement) + - [ ] count set bits + - [4 ways to count bits in a byte (video)](https://youtu.be/Hzuzo9NJrlc) + - [Count Bits](https://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetKernighan) + - [How To Count The Number Of Set Bits In a 32 Bit Integer](http://stackoverflow.com/questions/109023/how-to-count-the-number-of-set-bits-in-a-32-bit-integer) + - [ ] swap values: + - [Swap](https://bits.stephan-brumme.com/swap.html) + - [ ] absolute value: + - [Absolute Integer](https://bits.stephan-brumme.com/absInteger.html) ## Trees - ### Trees - Notes & Background - - - [ ] [Series: Core Trees (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/ovovP/core-trees) - - [ ] [Series: Trees (video)](https://www.coursera.org/learn/data-structures/lecture/95qda/trees) - - basic tree construction - - traversal - - manipulation algorithms - - [ ] [BFS(breadth-first search) and DFS(depth-first search) (video)](https://www.youtube.com/watch?v=uWL6FJhq5fM) - - BFS notes: - - level order (BFS, using queue) - - time complexity: O(n) - - space complexity: best: O(1), worst: O(n/2)=O(n) - - DFS notes: - - time complexity: O(n) - - space complexity: - best: O(log n) - avg. height of tree - worst: O(n) - - inorder (DFS: left, self, right) - - postorder (DFS: left, right, self) - - preorder (DFS: self, left, right) + - [ ] [Series: Core Trees (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/ovovP/core-trees) + - [ ] [Series: Trees (video)](https://www.coursera.org/learn/data-structures/lecture/95qda/trees) + - basic tree construction + - traversal + - manipulation algorithms + - [ ] [BFS(breadth-first search) and DFS(depth-first search) (video)](https://www.youtube.com/watch?v=uWL6FJhq5fM) + - BFS notes: + - level order (BFS, using queue) + - time complexity: O(n) + - space complexity: best: O(1), worst: O(n/2)=O(n) + - DFS notes: + - time complexity: O(n) + - space complexity: + best: O(log n) - avg. height of tree + worst: O(n) + - inorder (DFS: left, self, right) + - postorder (DFS: left, right, self) + - preorder (DFS: self, left, right) - ### Binary search trees: BSTs - - - [ ] [Binary Search Tree Review (video)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) - - [ ] [Series (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees) - - starts with symbol table and goes through BST applications - - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction) - - [ ] [MIT (video)](https://www.youtube.com/watch?v=9Jry5-82I68) - - C/C++: - - [ ] [Binary search tree - Implementation in C/C++ (video)](https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28) - - [ ] [BST implementation - memory allocation in stack and heap (video)](https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29) - - [ ] [Find min and max element in a binary search tree (video)](https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) - - [ ] [Find height of a binary tree (video)](https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31) - - [ ] [Binary tree traversal - breadth-first and depth-first strategies (video)](https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32) - - [ ] [Binary tree: Level Order Traversal (video)](https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) - - [ ] [Binary tree traversal: Preorder, Inorder, Postorder (video)](https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) - - [ ] [Check if a binary tree is binary search tree or not (video)](https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) - - [ ] [Delete a node from Binary Search Tree (video)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36) - - [ ] [Inorder Successor in a binary search tree (video)](https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) - - [ ] Implement: - - [ ] insert // insert value into tree - - [ ] get_node_count // get count of values stored - - [ ] print_values // prints the values in the tree, from min to max - - [ ] delete_tree - - [ ] is_in_tree // returns true if given value exists in the tree - - [ ] get_height // returns the height in nodes (single node's height is 1) - - [ ] get_min // returns the minimum value stored in the tree - - [ ] get_max // returns the maximum value stored in the tree - - [ ] is_binary_search_tree - - [ ] delete_value - - [ ] get_successor // returns next-highest value in tree after given value, -1 if none + - [ ] [Binary Search Tree Review (video)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) + - [ ] [Series (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees) + - starts with symbol table and goes through BST applications + - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction) + - [ ] [MIT (video)](https://www.youtube.com/watch?v=9Jry5-82I68) + - C/C++: + - [ ] [Binary search tree - Implementation in C/C++ (video)](https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28) + - [ ] [BST implementation - memory allocation in stack and heap (video)](https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29) + - [ ] [Find min and max element in a binary search tree (video)](https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) + - [ ] [Find height of a binary tree (video)](https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31) + - [ ] [Binary tree traversal - breadth-first and depth-first strategies (video)](https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32) + - [ ] [Binary tree: Level Order Traversal (video)](https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) + - [ ] [Binary tree traversal: Preorder, Inorder, Postorder (video)](https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) + - [ ] [Check if a binary tree is binary search tree or not (video)](https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) + - [ ] [Delete a node from Binary Search Tree (video)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36) + - [ ] [Inorder Successor in a binary search tree (video)](https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) + - [ ] Implement: + - [ ] insert // insert value into tree + - [ ] get_node_count // get count of values stored + - [ ] print_values // prints the values in the tree, from min to max + - [ ] delete_tree + - [ ] is_in_tree // returns true if given value exists in the tree + - [ ] get_height // returns the height in nodes (single node's height is 1) + - [ ] get_min // returns the minimum value stored in the tree + - [ ] get_max // returns the maximum value stored in the tree + - [ ] is_binary_search_tree + - [ ] delete_value + - [ ] get_successor // returns next-highest value in tree after given value, -1 if none - ### Heap / Priority Queue / Binary Heap - - visualized as a tree, but is usually linear in storage (array, linked list) - - [ ] [Heap]() - - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction) - - [ ] [Naive Implementations (video)](https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations) - - [ ] [Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees) - - [ ] [Tree Height Remark (video)](https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark) - - [ ] [Basic Operations (video)](https://www.coursera.org/learn/data-structures/lecture/0g1dl/basic-operations) - - [ ] [Complete Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/gl5Ni/complete-binary-trees) - - [ ] [Pseudocode (video)](https://www.coursera.org/learn/data-structures/lecture/HxQo9/pseudocode) - - [ ] [Heap Sort - jumps to start (video)](https://youtu.be/odNJmw5TOEE?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3291) - - [ ] [Heap Sort (video)](https://www.coursera.org/learn/data-structures/lecture/hSzMO/heap-sort) - - [ ] [Building a heap (video)](https://www.coursera.org/learn/data-structures/lecture/dwrOS/building-a-heap) - - [ ] [MIT: Heaps and Heap Sort (video)](https://www.youtube.com/watch?v=B7hVxCmfPtM&index=4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [ ] [CS 61B Lecture 24: Priority Queues (video)](https://archive.org/details/ucberkeley_webcast_yIUFT6AKBGE) - - [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw) - - [ ] Implement a max-heap: - - [ ] insert - - [ ] sift_up - needed for insert - - [ ] get_max - returns the max item, without removing it - - [ ] get_size() - return number of elements stored - - [ ] is_empty() - returns true if heap contains no elements - - [ ] extract_max - returns the max item, removing it - - [ ] sift_down - needed for extract_max - - [ ] remove(i) - removes item at index x - - [ ] heapify - create a heap from an array of elements, needed for heap_sort - - [ ] heap_sort() - take an unsorted array and turn it into a sorted array in-place using a max heap - - note: using a min heap instead would save operations, but double the space needed (cannot do in-place). + - visualized as a tree, but is usually linear in storage (array, linked list) + - [ ] [Heap](https://en.wikipedia.org/wiki/Heap_(data_structure)) + - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction) + - [ ] [Naive Implementations (video)](https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations) + - [ ] [Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees) + - [ ] [Tree Height Remark (video)](https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark) + - [ ] [Basic Operations (video)](https://www.coursera.org/learn/data-structures/lecture/0g1dl/basic-operations) + - [ ] [Complete Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/gl5Ni/complete-binary-trees) + - [ ] [Pseudocode (video)](https://www.coursera.org/learn/data-structures/lecture/HxQo9/pseudocode) + - [ ] [Heap Sort - jumps to start (video)](https://youtu.be/odNJmw5TOEE?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3291) + - [ ] [Heap Sort (video)](https://www.coursera.org/learn/data-structures/lecture/hSzMO/heap-sort) + - [ ] [Building a heap (video)](https://www.coursera.org/learn/data-structures/lecture/dwrOS/building-a-heap) + - [ ] [MIT: Heaps and Heap Sort (video)](https://www.youtube.com/watch?v=B7hVxCmfPtM&index=4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) + - [ ] [CS 61B Lecture 24: Priority Queues (video)](https://archive.org/details/ucberkeley_webcast_yIUFT6AKBGE) + - [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw) + - [ ] Implement a max-heap: + - [ ] insert + - [ ] sift_up - needed for insert + - [ ] get_max - returns the max item, without removing it + - [ ] get_size() - return number of elements stored + - [ ] is_empty() - returns true if heap contains no elements + - [ ] extract_max - returns the max item, removing it + - [ ] sift_down - needed for extract_max + - [ ] remove(i) - removes item at index x + - [ ] heapify - create a heap from an array of elements, needed for heap_sort + - [ ] heap_sort() - take an unsorted array and turn it into a sorted array in-place using a max heap + - note: using a min heap instead would save operations, but double the space needed (cannot do in-place). ## Sorting - [ ] Notes: - - - Implement sorts & know best case/worst case, average complexity of each: - - no bubble sort - it's terrible - O(n^2), except when n <= 16 - - [ ] stability in sorting algorithms ("Is Quicksort stable?") - - [Sorting Algorithm Stability](https://en.wikipedia.org/wiki/Sorting_algorithm#Stability) - - [Stability In Sorting Algorithms](http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms) - - [Stability In Sorting Algorithms](http://www.geeksforgeeks.org/stability-in-sorting-algorithms/) - - [Sorting Algorithms - Stability](http://homepages.math.uic.edu/~leon/cs-mcs401-s08/handouts/stability.pdf) - - [ ] Which algorithms can be used on linked lists? Which on arrays? Which on both? - - I wouldn't recommend sorting a linked list, but merge sort is doable. - - [Merge Sort For Linked List](http://www.geeksforgeeks.org/merge-sort-for-linked-list/) + - Implement sorts & know best case/worst case, average complexity of each: + - no bubble sort - it's terrible - O(n^2), except when n <= 16 + - [ ] stability in sorting algorithms ("Is Quicksort stable?") + - [Sorting Algorithm Stability](https://en.wikipedia.org/wiki/Sorting_algorithm#Stability) + - [Stability In Sorting Algorithms](http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms) + - [Stability In Sorting Algorithms](http://www.geeksforgeeks.org/stability-in-sorting-algorithms/) + - [Sorting Algorithms - Stability](http://homepages.math.uic.edu/~leon/cs-mcs401-s08/handouts/stability.pdf) + - [ ] Which algorithms can be used on linked lists? Which on arrays? Which on both? + - I wouldn't recommend sorting a linked list, but merge sort is doable. + - [Merge Sort For Linked List](http://www.geeksforgeeks.org/merge-sort-for-linked-list/) - For heapsort, see Heap data structure above. Heap sort is great, but not stable. - [ ] [Sedgewick - Mergesort (5 videos)](https://www.coursera.org/learn/algorithms-part1/home/week/3) - - - [ ] [1. Mergesort](https://www.coursera.org/learn/algorithms-part1/lecture/ARWDq/mergesort) - - [ ] [2. Bottom up Mergesort](https://www.coursera.org/learn/algorithms-part1/lecture/PWNEl/bottom-up-mergesort) - - [ ] [3. Sorting Complexity](https://www.coursera.org/learn/algorithms-part1/lecture/xAltF/sorting-complexity) - - [ ] [4. Comparators](https://www.coursera.org/learn/algorithms-part1/lecture/9FYhS/comparators) - - [ ] [5. Stability](https://www.coursera.org/learn/algorithms-part1/lecture/pvvLZ/stability) + - [ ] [1. Mergesort](https://www.coursera.org/learn/algorithms-part1/lecture/ARWDq/mergesort) + - [ ] [2. Bottom up Mergesort](https://www.coursera.org/learn/algorithms-part1/lecture/PWNEl/bottom-up-mergesort) + - [ ] [3. Sorting Complexity](https://www.coursera.org/learn/algorithms-part1/lecture/xAltF/sorting-complexity) + - [ ] [4. Comparators](https://www.coursera.org/learn/algorithms-part1/lecture/9FYhS/comparators) + - [ ] [5. Stability](https://www.coursera.org/learn/algorithms-part1/lecture/pvvLZ/stability) - [ ] [Sedgewick - Quicksort (4 videos)](https://www.coursera.org/learn/algorithms-part1/home/week/3) - - - [ ] [1. Quicksort](https://www.coursera.org/learn/algorithms-part1/lecture/vjvnC/quicksort) - - [ ] [2. Selection](https://www.coursera.org/learn/algorithms-part1/lecture/UQxFT/selection) - - [ ] [3. Duplicate Keys](https://www.coursera.org/learn/algorithms-part1/lecture/XvjPd/duplicate-keys) - - [ ] [4. System Sorts](https://www.coursera.org/learn/algorithms-part1/lecture/QBNZ7/system-sorts) + - [ ] [1. Quicksort](https://www.coursera.org/learn/algorithms-part1/lecture/vjvnC/quicksort) + - [ ] [2. Selection](https://www.coursera.org/learn/algorithms-part1/lecture/UQxFT/selection) + - [ ] [3. Duplicate Keys](https://www.coursera.org/learn/algorithms-part1/lecture/XvjPd/duplicate-keys) + - [ ] [4. System Sorts](https://www.coursera.org/learn/algorithms-part1/lecture/QBNZ7/system-sorts) - [ ] UC Berkeley: - - - [ ] [CS 61B Lecture 29: Sorting I (video)](https://archive.org/details/ucberkeley_webcast_EiUvYS2DT6I) - - [ ] [CS 61B Lecture 30: Sorting II (video)](https://archive.org/details/ucberkeley_webcast_2hTY3t80Qsk) - - [ ] [CS 61B Lecture 32: Sorting III (video)](https://archive.org/details/ucberkeley_webcast_Y6LOLpxg6Dc) - - [ ] [CS 61B Lecture 33: Sorting V (video)](https://archive.org/details/ucberkeley_webcast_qNMQ4ly43p4) + - [ ] [CS 61B Lecture 29: Sorting I (video)](https://archive.org/details/ucberkeley_webcast_EiUvYS2DT6I) + - [ ] [CS 61B Lecture 30: Sorting II (video)](https://archive.org/details/ucberkeley_webcast_2hTY3t80Qsk) + - [ ] [CS 61B Lecture 32: Sorting III (video)](https://archive.org/details/ucberkeley_webcast_Y6LOLpxg6Dc) + - [ ] [CS 61B Lecture 33: Sorting V (video)](https://archive.org/details/ucberkeley_webcast_qNMQ4ly43p4) - [ ] [Bubble Sort (video)](https://www.youtube.com/watch?v=P00xJgWzz2c&index=1&list=PL89B61F78B552C1AB) - [ ] [Analyzing Bubble Sort (video)](https://www.youtube.com/watch?v=ni_zk257Nqo&index=7&list=PL89B61F78B552C1AB) @@ -791,35 +777,33 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - [ ] [Selection Sort (video)](https://www.youtube.com/watch?v=6nDMgr0-Yyo&index=8&list=PL89B61F78B552C1AB) - [ ] Merge sort code: - - [ ] [Using output array (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/sorting/mergesort.c) - - [ ] [Using output array (Python)](https://github.com/jwasham/practice-python/blob/master/merge_sort/merge_sort.py) - - [ ] [In-place (C++)](https://github.com/jwasham/practice-cpp/blob/master/merge_sort/merge_sort.cc) + - [ ] [Using output array (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/sorting/mergesort.c) + - [ ] [Using output array (Python)](https://github.com/jwasham/practice-python/blob/master/merge_sort/merge_sort.py) + - [ ] [In-place (C++)](https://github.com/jwasham/practice-cpp/blob/master/merge_sort/merge_sort.cc) - [ ] Quick sort code: - - - [ ] [Implementation (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/randomization/quick.c) - - [ ] [Implementation (C)](https://github.com/jwasham/practice-c/blob/master/quick_sort/quick_sort.c) - - [ ] [Implementation (Python)](https://github.com/jwasham/practice-python/blob/master/quick_sort/quick_sort.py) + - [ ] [Implementation (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/randomization/quick.c) + - [ ] [Implementation (C)](https://github.com/jwasham/practice-c/blob/master/quick_sort/quick_sort.c) + - [ ] [Implementation (Python)](https://github.com/jwasham/practice-python/blob/master/quick_sort/quick_sort.py) - [ ] Implement: - - - [ ] Mergesort: O(n log n) average and worst case - - [ ] Quicksort O(n log n) average case - - Selection sort and insertion sort are both O(n^2) average and worst case - - For heapsort, see Heap data structure above. + - [ ] Mergesort: O(n log n) average and worst case + - [ ] Quicksort O(n log n) average case + - Selection sort and insertion sort are both O(n^2) average and worst case + - For heapsort, see Heap data structure above. - [ ] Not required, but I recommended them: - - [ ] [Sedgewick - Radix Sorts (6 videos)](https://www.coursera.org/learn/algorithms-part2/home/week/3) - - [ ] [1. Strings in Java](https://www.coursera.org/learn/algorithms-part2/lecture/vGHvb/strings-in-java) - - [ ] [2. Key Indexed Counting](https://www.coursera.org/learn/algorithms-part2/lecture/2pi1Z/key-indexed-counting) - - [ ] [3. Least Significant Digit First String Radix Sort](https://www.coursera.org/learn/algorithms-part2/lecture/c1U7L/lsd-radix-sort) - - [ ] [4. Most Significant Digit First String Radix Sort](https://www.coursera.org/learn/algorithms-part2/lecture/gFxwG/msd-radix-sort) - - [ ] [5. 3 Way Radix Quicksort](https://www.coursera.org/learn/algorithms-part2/lecture/crkd5/3-way-radix-quicksort) - - [ ] [6. Suffix Arrays](https://www.coursera.org/learn/algorithms-part2/lecture/TH18W/suffix-arrays) - - [ ] [Radix Sort](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#radixSort) - - [ ] [Radix Sort (video)](https://www.youtube.com/watch?v=xhr26ia4k38) - - [ ] [Radix Sort, Counting Sort (linear time given constraints) (video)](https://www.youtube.com/watch?v=Nz1KZXbghj8&index=7&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [ ] [Randomization: Matrix Multiply, Quicksort, Freivalds' algorithm (video)](https://www.youtube.com/watch?v=cNB2lADK3_s&index=8&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - - [ ] [Sorting in Linear Time (video)](https://www.youtube.com/watch?v=pOKy3RZbSws&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=14) + - [ ] [Sedgewick - Radix Sorts (6 videos)](https://www.coursera.org/learn/algorithms-part2/home/week/3) + - [ ] [1. Strings in Java](https://www.coursera.org/learn/algorithms-part2/lecture/vGHvb/strings-in-java) + - [ ] [2. Key Indexed Counting](https://www.coursera.org/learn/algorithms-part2/lecture/2pi1Z/key-indexed-counting) + - [ ] [3. Least Significant Digit First String Radix Sort](https://www.coursera.org/learn/algorithms-part2/lecture/c1U7L/lsd-radix-sort) + - [ ] [4. Most Significant Digit First String Radix Sort](https://www.coursera.org/learn/algorithms-part2/lecture/gFxwG/msd-radix-sort) + - [ ] [5. 3 Way Radix Quicksort](https://www.coursera.org/learn/algorithms-part2/lecture/crkd5/3-way-radix-quicksort) + - [ ] [6. Suffix Arrays](https://www.coursera.org/learn/algorithms-part2/lecture/TH18W/suffix-arrays) + - [ ] [Radix Sort](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#radixSort) + - [ ] [Radix Sort (video)](https://www.youtube.com/watch?v=xhr26ia4k38) + - [ ] [Radix Sort, Counting Sort (linear time given constraints) (video)](https://www.youtube.com/watch?v=Nz1KZXbghj8&index=7&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) + - [ ] [Randomization: Matrix Multiply, Quicksort, Freivalds' algorithm (video)](https://www.youtube.com/watch?v=cNB2lADK3_s&index=8&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) + - [ ] [Sorting in Linear Time (video)](https://www.youtube.com/watch?v=pOKy3RZbSws&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=14) As a summary, here is a visual representation of [15 sorting algorithms](https://www.youtube.com/watch?v=kPRA0W1kECg). If you need more detail on this subject, see "Sorting" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects) @@ -829,328 +813,312 @@ If you need more detail on this subject, see "Sorting" section in [Additional De Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were. - Notes: - - - There are 4 basic ways to represent a graph in memory: - - objects and pointers - - adjacency matrix - - adjacency list - - adjacency map - - Familiarize yourself with each representation and its pros & cons - - BFS and DFS - know their computational complexity, their tradeoffs, and how to implement them in real code - - When asked a question, look for a graph-based solution first, then move on if none. + - There are 4 basic ways to represent a graph in memory: + - objects and pointers + - adjacency matrix + - adjacency list + - adjacency map + - Familiarize yourself with each representation and its pros & cons + - BFS and DFS - know their computational complexity, their tradeoffs, and how to implement them in real code + - When asked a question, look for a graph-based solution first, then move on if none. - [ ] MIT(videos): - - - [ ] [Breadth-First Search](https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13) - - [ ] [Depth-First Search](https://www.youtube.com/watch?v=AfSk24UTFS8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=14) + - [ ] [Breadth-First Search](https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13) + - [ ] [Depth-First Search](https://www.youtube.com/watch?v=AfSk24UTFS8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=14) - [ ] Skiena Lectures - great intro: - - - [ ] [CSE373 2012 - Lecture 11 - Graph Data Structures (video)](https://www.youtube.com/watch?v=OiXxhDrFruw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=11) - - [ ] [CSE373 2012 - Lecture 12 - Breadth-First Search (video)](https://www.youtube.com/watch?v=g5vF8jscteo&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=12) - - [ ] [CSE373 2012 - Lecture 13 - Graph Algorithms (video)](https://www.youtube.com/watch?v=S23W6eTcqdY&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=13) - - [ ] [CSE373 2012 - Lecture 14 - Graph Algorithms (con't) (video)](https://www.youtube.com/watch?v=WitPBKGV0HY&index=14&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [ ] [CSE373 2012 - Lecture 15 - Graph Algorithms (con't 2) (video)](https://www.youtube.com/watch?v=ia1L30l7OIg&index=15&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [ ] [CSE373 2012 - Lecture 16 - Graph Algorithms (con't 3) (video)](https://www.youtube.com/watch?v=jgDOQq6iWy8&index=16&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [ ] [CSE373 2012 - Lecture 11 - Graph Data Structures (video)](https://www.youtube.com/watch?v=OiXxhDrFruw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=11) + - [ ] [CSE373 2012 - Lecture 12 - Breadth-First Search (video)](https://www.youtube.com/watch?v=g5vF8jscteo&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=12) + - [ ] [CSE373 2012 - Lecture 13 - Graph Algorithms (video)](https://www.youtube.com/watch?v=S23W6eTcqdY&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=13) + - [ ] [CSE373 2012 - Lecture 14 - Graph Algorithms (con't) (video)](https://www.youtube.com/watch?v=WitPBKGV0HY&index=14&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [ ] [CSE373 2012 - Lecture 15 - Graph Algorithms (con't 2) (video)](https://www.youtube.com/watch?v=ia1L30l7OIg&index=15&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [ ] [CSE373 2012 - Lecture 16 - Graph Algorithms (con't 3) (video)](https://www.youtube.com/watch?v=jgDOQq6iWy8&index=16&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - [ ] Graphs (review and more): - - [ ] [6.006 Single-Source Shortest Paths Problem (video)](https://www.youtube.com/watch?v=Aa2sqUhIn-E&index=15&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [ ] [6.006 Dijkstra (video)](https://www.youtube.com/watch?v=2E7MmKv0Y24&index=16&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [ ] [6.006 Bellman-Ford (video)](https://www.youtube.com/watch?v=ozsuci5pIso&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=17) - - [ ] [6.006 Speeding Up Dijkstra (video)](https://www.youtube.com/watch?v=CHvQ3q_gJ7E&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=18) - - [ ] [Aduni: Graph Algorithms I - Topological Sorting, Minimum Spanning Trees, Prim's Algorithm - Lecture 6 (video)](https://www.youtube.com/watch?v=i_AQT_XfvD8&index=6&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) - - [ ] [Aduni: Graph Algorithms II - DFS, BFS, Kruskal's Algorithm, Union Find Data Structure - Lecture 7 (video)](https://www.youtube.com/watch?v=ufj5_bppBsA&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=7) - - [ ] [Aduni: Graph Algorithms III: Shortest Path - Lecture 8 (video)](https://www.youtube.com/watch?v=DiedsPsMKXc&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=8) - - [ ] [Aduni: Graph Alg. IV: Intro to geometric algorithms - Lecture 9 (video)](https://www.youtube.com/watch?v=XIAQRlNkJAw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=9) - - [ ] ~~[CS 61B 2014 (starting at 58:09) (video)](https://youtu.be/dgjX4HdMI-Q?list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&t=3489)~~ - - [ ] [CS 61B 2014: Weighted graphs (video)](https://archive.org/details/ucberkeley_webcast_zFbq8vOZ_0k) - - [ ] [Greedy Algorithms: Minimum Spanning Tree (video)](https://www.youtube.com/watch?v=tKwnms5iRBU&index=16&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - - [ ] [Strongly Connected Components Kosaraju's Algorithm Graph Algorithm (video)](https://www.youtube.com/watch?v=RpgcYiky7uw) + - [ ] [6.006 Single-Source Shortest Paths Problem (video)](https://www.youtube.com/watch?v=Aa2sqUhIn-E&index=15&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) + - [ ] [6.006 Dijkstra (video)](https://www.youtube.com/watch?v=2E7MmKv0Y24&index=16&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) + - [ ] [6.006 Bellman-Ford (video)](https://www.youtube.com/watch?v=ozsuci5pIso&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=17) + - [ ] [6.006 Speeding Up Dijkstra (video)](https://www.youtube.com/watch?v=CHvQ3q_gJ7E&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=18) + - [ ] [Aduni: Graph Algorithms I - Topological Sorting, Minimum Spanning Trees, Prim's Algorithm - Lecture 6 (video)]( https://www.youtube.com/watch?v=i_AQT_XfvD8&index=6&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) + - [ ] [Aduni: Graph Algorithms II - DFS, BFS, Kruskal's Algorithm, Union Find Data Structure - Lecture 7 (video)]( https://www.youtube.com/watch?v=ufj5_bppBsA&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=7) + - [ ] [Aduni: Graph Algorithms III: Shortest Path - Lecture 8 (video)](https://www.youtube.com/watch?v=DiedsPsMKXc&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=8) + - [ ] [Aduni: Graph Alg. IV: Intro to geometric algorithms - Lecture 9 (video)](https://www.youtube.com/watch?v=XIAQRlNkJAw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=9) + - [ ] ~~[CS 61B 2014 (starting at 58:09) (video)](https://youtu.be/dgjX4HdMI-Q?list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&t=3489)~~ + - [ ] [CS 61B 2014: Weighted graphs (video)](https://archive.org/details/ucberkeley_webcast_zFbq8vOZ_0k) + - [ ] [Greedy Algorithms: Minimum Spanning Tree (video)](https://www.youtube.com/watch?v=tKwnms5iRBU&index=16&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) + - [ ] [Strongly Connected Components Kosaraju's Algorithm Graph Algorithm (video)](https://www.youtube.com/watch?v=RpgcYiky7uw) - Full Coursera Course: - - - [ ] [Algorithms on Graphs (video)](https://www.coursera.org/learn/algorithms-on-graphs/home/welcome) + - [ ] [Algorithms on Graphs (video)](https://www.coursera.org/learn/algorithms-on-graphs/home/welcome) - I'll implement: - - [ ] DFS with adjacency list (recursive) - - [ ] DFS with adjacency list (iterative with stack) - - [ ] DFS with adjacency matrix (recursive) - - [ ] DFS with adjacency matrix (iterative with stack) - - [ ] BFS with adjacency list - - [ ] BFS with adjacency matrix - - [ ] single-source shortest path (Dijkstra) - - [ ] minimum spanning tree - - DFS-based algorithms (see Aduni videos above): - - [ ] check for cycle (needed for topological sort, since we'll check for cycle before starting) - - [ ] topological sort - - [ ] count connected components in a graph - - [ ] list strongly connected components - - [ ] check for bipartite graph + - [ ] DFS with adjacency list (recursive) + - [ ] DFS with adjacency list (iterative with stack) + - [ ] DFS with adjacency matrix (recursive) + - [ ] DFS with adjacency matrix (iterative with stack) + - [ ] BFS with adjacency list + - [ ] BFS with adjacency matrix + - [ ] single-source shortest path (Dijkstra) + - [ ] minimum spanning tree + - DFS-based algorithms (see Aduni videos above): + - [ ] check for cycle (needed for topological sort, since we'll check for cycle before starting) + - [ ] topological sort + - [ ] count connected components in a graph + - [ ] list strongly connected components + - [ ] check for bipartite graph ## Even More Knowledge - ### Recursion - - - [ ] Stanford lectures on recursion & backtracking: - - [ ] [Lecture 8 | Programming Abstractions (video)](https://www.youtube.com/watch?v=gl3emqCuueQ&list=PLFE6E58F856038C69&index=8) - - [ ] [Lecture 9 | Programming Abstractions (video)](https://www.youtube.com/watch?v=uFJhEPrbycQ&list=PLFE6E58F856038C69&index=9) - - [ ] [Lecture 10 | Programming Abstractions (video)](https://www.youtube.com/watch?v=NdF1QDTRkck&index=10&list=PLFE6E58F856038C69) - - [ ] [Lecture 11 | Programming Abstractions (video)](https://www.youtube.com/watch?v=p-gpaIGRCQI&list=PLFE6E58F856038C69&index=11) - - when it is appropriate to use it - - how is tail recursion better than not? - - [ ] [What Is Tail Recursion Why Is It So Bad?](https://www.quora.com/What-is-tail-recursion-Why-is-it-so-bad) - - [ ] [Tail Recursion (video)](https://www.youtube.com/watch?v=L1jjXGfxozc) + - [ ] Stanford lectures on recursion & backtracking: + - [ ] [Lecture 8 | Programming Abstractions (video)](https://www.youtube.com/watch?v=gl3emqCuueQ&list=PLFE6E58F856038C69&index=8) + - [ ] [Lecture 9 | Programming Abstractions (video)](https://www.youtube.com/watch?v=uFJhEPrbycQ&list=PLFE6E58F856038C69&index=9) + - [ ] [Lecture 10 | Programming Abstractions (video)](https://www.youtube.com/watch?v=NdF1QDTRkck&index=10&list=PLFE6E58F856038C69) + - [ ] [Lecture 11 | Programming Abstractions (video)](https://www.youtube.com/watch?v=p-gpaIGRCQI&list=PLFE6E58F856038C69&index=11) + - when it is appropriate to use it + - how is tail recursion better than not? + - [ ] [What Is Tail Recursion Why Is It So Bad?](https://www.quora.com/What-is-tail-recursion-Why-is-it-so-bad) + - [ ] [Tail Recursion (video)](https://www.youtube.com/watch?v=L1jjXGfxozc) - ### Dynamic Programming - - - You probably won't see any dynamic programming problems in your interview, but it's worth being able to recognize a problem as being a candidate for dynamic programming. - - This subject can be pretty difficult, as each DP soluble problem must be defined as a recursion relation, and coming up with it can be tricky. - - I suggest looking at many examples of DP problems until you have a solid understanding of the pattern involved. - - [ ] Videos: - - the Skiena videos can be hard to follow since he sometimes uses the whiteboard, which is too small to see - - [ ] [Skiena: CSE373 2012 - Lecture 19 - Introduction to Dynamic Programming (video)](https://youtu.be/Qc2ieXRgR0k?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1718) - - [ ] [Skiena: CSE373 2012 - Lecture 20 - Edit Distance (video)](https://youtu.be/IsmMhMdyeGY?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=2749) - - [ ] [Skiena: CSE373 2012 - Lecture 21 - Dynamic Programming Examples (video)](https://youtu.be/o0V9eYF4UI8?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=406) - - [ ] [Skiena: CSE373 2012 - Lecture 22 - Applications of Dynamic Programming (video)](https://www.youtube.com/watch?v=dRbMC1Ltl3A&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=22) - - [ ] [Simonson: Dynamic Programming 0 (starts at 59:18) (video)](https://youtu.be/J5aJEcOr6Eo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3558) - - [ ] [Simonson: Dynamic Programming I - Lecture 11 (video)](https://www.youtube.com/watch?v=0EzHjQ_SOeU&index=11&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) - - [ ] [Simonson: Dynamic programming II - Lecture 12 (video)](https://www.youtube.com/watch?v=v1qiRwuJU7g&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=12) - - [ ] List of individual DP problems (each is short): - [Dynamic Programming (video)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr) - - [ ] Yale Lecture notes: - - [ ] [Dynamic Programming](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#dynamicProgramming) - - [ ] Coursera: - - [ ] [The RNA secondary structure problem (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/80RrW/the-rna-secondary-structure-problem) - - [ ] [A dynamic programming algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/PSonq/a-dynamic-programming-algorithm) - - [ ] [Illustrating the DP algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/oUEK2/illustrating-the-dp-algorithm) - - [ ] [Running time of the DP algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/nfK2r/running-time-of-the-dp-algorithm) - - [ ] [DP vs. recursive implementation (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/M999a/dp-vs-recursive-implementation) - - [ ] [Global pairwise sequence alignment (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/UZ7o6/global-pairwise-sequence-alignment) - - [ ] [Local pairwise sequence alignment (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/WnNau/local-pairwise-sequence-alignment) + - You probably won't see any dynamic programming problems in your interview, but it's worth being able to recognize a problem as being a candidate for dynamic programming. + - This subject can be pretty difficult, as each DP soluble problem must be defined as a recursion relation, and coming up with it can be tricky. + - I suggest looking at many examples of DP problems until you have a solid understanding of the pattern involved. + - [ ] Videos: + - the Skiena videos can be hard to follow since he sometimes uses the whiteboard, which is too small to see + - [ ] [Skiena: CSE373 2012 - Lecture 19 - Introduction to Dynamic Programming (video)](https://youtu.be/Qc2ieXRgR0k?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1718) + - [ ] [Skiena: CSE373 2012 - Lecture 20 - Edit Distance (video)](https://youtu.be/IsmMhMdyeGY?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=2749) + - [ ] [Skiena: CSE373 2012 - Lecture 21 - Dynamic Programming Examples (video)](https://youtu.be/o0V9eYF4UI8?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=406) + - [ ] [Skiena: CSE373 2012 - Lecture 22 - Applications of Dynamic Programming (video)](https://www.youtube.com/watch?v=dRbMC1Ltl3A&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=22) + - [ ] [Simonson: Dynamic Programming 0 (starts at 59:18) (video)](https://youtu.be/J5aJEcOr6Eo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3558) + - [ ] [Simonson: Dynamic Programming I - Lecture 11 (video)](https://www.youtube.com/watch?v=0EzHjQ_SOeU&index=11&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) + - [ ] [Simonson: Dynamic programming II - Lecture 12 (video)](https://www.youtube.com/watch?v=v1qiRwuJU7g&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=12) + - [ ] List of individual DP problems (each is short): + [Dynamic Programming (video)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr) + - [ ] Yale Lecture notes: + - [ ] [Dynamic Programming](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#dynamicProgramming) + - [ ] Coursera: + - [ ] [The RNA secondary structure problem (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/80RrW/the-rna-secondary-structure-problem) + - [ ] [A dynamic programming algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/PSonq/a-dynamic-programming-algorithm) + - [ ] [Illustrating the DP algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/oUEK2/illustrating-the-dp-algorithm) + - [ ] [Running time of the DP algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/nfK2r/running-time-of-the-dp-algorithm) + - [ ] [DP vs. recursive implementation (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/M999a/dp-vs-recursive-implementation) + - [ ] [Global pairwise sequence alignment (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/UZ7o6/global-pairwise-sequence-alignment) + - [ ] [Local pairwise sequence alignment (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/WnNau/local-pairwise-sequence-alignment) - ### Object-Oriented Programming - - - [ ] [Optional: UML 2.0 Series (video)](https://www.youtube.com/watch?v=OkC7HKtiZC0&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc) - - [ ] SOLID OOP Principles: [SOLID Principles (video)](https://www.youtube.com/playlist?list=PL4CE9F710017EA77A) + - [ ] [Optional: UML 2.0 Series (video)](https://www.youtube.com/watch?v=OkC7HKtiZC0&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc) + - [ ] SOLID OOP Principles: [SOLID Principles (video)](https://www.youtube.com/playlist?list=PL4CE9F710017EA77A) - ### Design patterns - - [ ] [Quick UML review (video)](https://www.youtube.com/watch?v=3cmzqZzwNDM&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc&index=3) - - [ ] Learn these patterns: - - [ ] strategy - - [ ] singleton - - [ ] adapter - - [ ] prototype - - [ ] decorator - - [ ] visitor - - [ ] factory, abstract factory - - [ ] facade - - [ ] observer - - [ ] proxy - - [ ] delegate - - [ ] command - - [ ] state - - [ ] memento - - [ ] iterator - - [ ] composite - - [ ] flyweight - - [ ] [Chapter 6 (Part 1) - Patterns (video)](https://youtu.be/LAP2A80Ajrg?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO&t=3344) - - [ ] [Chapter 6 (Part 2) - Abstraction-Occurrence, General Hierarchy, Player-Role, Singleton, Observer, Delegation (video)](https://www.youtube.com/watch?v=U8-PGsjvZc4&index=12&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO) - - [ ] [Chapter 6 (Part 3) - Adapter, Facade, Immutable, Read-Only Interface, Proxy (video)](https://www.youtube.com/watch?v=7sduBHuex4c&index=13&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO) - - [ ] [Series of videos (27 videos)](https://www.youtube.com/playlist?list=PLF206E906175C7E07) - - [ ] [Head First Design Patterns](https://www.amazon.com/Head-First-Design-Patterns-Freeman/dp/0596007124) - - I know the canonical book is "Design Patterns: Elements of Reusable Object-Oriented Software", but Head First is great for beginners to OO. - - [ ] [Handy reference: 101 Design Patterns & Tips for Developers](https://sourcemaking.com/design-patterns-and-tips) - - [ ] [Design patterns for humans](https://github.com/kamranahmedse/design-patterns-for-humans#structural-design-patterns) + - [ ] [Quick UML review (video)](https://www.youtube.com/watch?v=3cmzqZzwNDM&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc&index=3) + - [ ] Learn these patterns: + - [ ] strategy + - [ ] singleton + - [ ] adapter + - [ ] prototype + - [ ] decorator + - [ ] visitor + - [ ] factory, abstract factory + - [ ] facade + - [ ] observer + - [ ] proxy + - [ ] delegate + - [ ] command + - [ ] state + - [ ] memento + - [ ] iterator + - [ ] composite + - [ ] flyweight + - [ ] [Chapter 6 (Part 1) - Patterns (video)](https://youtu.be/LAP2A80Ajrg?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO&t=3344) + - [ ] [Chapter 6 (Part 2) - Abstraction-Occurrence, General Hierarchy, Player-Role, Singleton, Observer, Delegation (video)](https://www.youtube.com/watch?v=U8-PGsjvZc4&index=12&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO) + - [ ] [Chapter 6 (Part 3) - Adapter, Facade, Immutable, Read-Only Interface, Proxy (video)](https://www.youtube.com/watch?v=7sduBHuex4c&index=13&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO) + - [ ] [Series of videos (27 videos)](https://www.youtube.com/playlist?list=PLF206E906175C7E07) + - [ ] [Head First Design Patterns](https://www.amazon.com/Head-First-Design-Patterns-Freeman/dp/0596007124) + - I know the canonical book is "Design Patterns: Elements of Reusable Object-Oriented Software", but Head First is great for beginners to OO. + - [ ] [Handy reference: 101 Design Patterns & Tips for Developers](https://sourcemaking.com/design-patterns-and-tips) + - [ ] [Design patterns for humans](https://github.com/kamranahmedse/design-patterns-for-humans#structural-design-patterns) -* ### Combinatorics (n choose k) & Probability - - [ ] [Math Skills: How to find Factorial, Permutation and Combination (Choose) (video)](https://www.youtube.com/watch?v=8RRo6Ti9d0U) - - [ ] [Make School: Probability (video)](https://www.youtube.com/watch?v=sZkAAk9Wwa4) - - [ ] [Make School: More Probability and Markov Chains (video)](https://www.youtube.com/watch?v=dNaJg-mLobQ) - - [ ] Khan Academy: - - Course layout: - - [ ] [Basic Theoretical Probability](https://www.khanacademy.org/math/probability/probability-and-combinatorics-topic) - - Just the videos - 41 (each are simple and each are short): - - [ ] [Probability Explained (video)](https://www.youtube.com/watch?v=uzkc-qNVoOk&list=PLC58778F28211FA19) +- ### Combinatorics (n choose k) & Probability + - [ ] [Math Skills: How to find Factorial, Permutation and Combination (Choose) (video)](https://www.youtube.com/watch?v=8RRo6Ti9d0U) + - [ ] [Make School: Probability (video)](https://www.youtube.com/watch?v=sZkAAk9Wwa4) + - [ ] [Make School: More Probability and Markov Chains (video)](https://www.youtube.com/watch?v=dNaJg-mLobQ) + - [ ] Khan Academy: + - Course layout: + - [ ] [Basic Theoretical Probability](https://www.khanacademy.org/math/probability/probability-and-combinatorics-topic) + - Just the videos - 41 (each are simple and each are short): + - [ ] [Probability Explained (video)](https://www.youtube.com/watch?v=uzkc-qNVoOk&list=PLC58778F28211FA19) -* ### NP, NP-Complete and Approximation Algorithms +- ### NP, NP-Complete and Approximation Algorithms + - Know about the most famous classes of NP-complete problems, such as traveling salesman and the knapsack problem, + and be able to recognize them when an interviewer asks you them in disguise. + - Know what NP-complete means. + - [ ] [Computational Complexity (video)](https://www.youtube.com/watch?v=moPtwq_cVH8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=23) + - [ ] Simonson: + - [ ] [Greedy Algs. II & Intro to NP Completeness (video)](https://youtu.be/qcGnJ47Smlo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=2939) + - [ ] [NP Completeness II & Reductions (video)](https://www.youtube.com/watch?v=e0tGC6ZQdQE&index=16&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) + - [ ] [NP Completeness III (Video)](https://www.youtube.com/watch?v=fCX1BGT3wjE&index=17&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) + - [ ] [NP Completeness IV (video)](https://www.youtube.com/watch?v=NKLDp3Rch3M&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=18) + - [ ] Skiena: + - [ ] [CSE373 2012 - Lecture 23 - Introduction to NP-Completeness (video)](https://youtu.be/KiK5TVgXbFg?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1508) + - [ ] [CSE373 2012 - Lecture 24 - NP-Completeness Proofs (video)](https://www.youtube.com/watch?v=27Al52X3hd4&index=24&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [ ] [CSE373 2012 - Lecture 25 - NP-Completeness Challenge (video)](https://www.youtube.com/watch?v=xCPH4gwIIXM&index=25&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [ ] [Complexity: P, NP, NP-completeness, Reductions (video)](https://www.youtube.com/watch?v=eHZifpgyH_4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=22) + - [ ] [Complexity: Approximation Algorithms (video)](https://www.youtube.com/watch?v=MEz1J9wY2iM&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=24) + - [ ] [Complexity: Fixed-Parameter Algorithms (video)](https://www.youtube.com/watch?v=4q-jmGrmxKs&index=25&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) + - Peter Norvig discusses near-optimal solutions to traveling salesman problem: + - [Jupyter Notebook](http://nbviewer.jupyter.org/url/norvig.com/ipython/TSP.ipynb) + - Pages 1048 - 1140 in CLRS if you have it. - - Know about the most famous classes of NP-complete problems, such as traveling salesman and the knapsack problem, - and be able to recognize them when an interviewer asks you them in disguise. - - Know what NP-complete means. - - [ ] [Computational Complexity (video)](https://www.youtube.com/watch?v=moPtwq_cVH8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=23) - - [ ] Simonson: - - [ ] [Greedy Algs. II & Intro to NP Completeness (video)](https://youtu.be/qcGnJ47Smlo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=2939) - - [ ] [NP Completeness II & Reductions (video)](https://www.youtube.com/watch?v=e0tGC6ZQdQE&index=16&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) - - [ ] [NP Completeness III (Video)](https://www.youtube.com/watch?v=fCX1BGT3wjE&index=17&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) - - [ ] [NP Completeness IV (video)](https://www.youtube.com/watch?v=NKLDp3Rch3M&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=18) - - [ ] Skiena: - - [ ] [CSE373 2012 - Lecture 23 - Introduction to NP-Completeness (video)](https://youtu.be/KiK5TVgXbFg?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1508) - - [ ] [CSE373 2012 - Lecture 24 - NP-Completeness Proofs (video)](https://www.youtube.com/watch?v=27Al52X3hd4&index=24&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [ ] [CSE373 2012 - Lecture 25 - NP-Completeness Challenge (video)](https://www.youtube.com/watch?v=xCPH4gwIIXM&index=25&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [ ] [Complexity: P, NP, NP-completeness, Reductions (video)](https://www.youtube.com/watch?v=eHZifpgyH_4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=22) - - [ ] [Complexity: Approximation Algorithms (video)](https://www.youtube.com/watch?v=MEz1J9wY2iM&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=24) - - [ ] [Complexity: Fixed-Parameter Algorithms (video)](https://www.youtube.com/watch?v=4q-jmGrmxKs&index=25&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - - Peter Norvig discusses near-optimal solutions to traveling salesman problem: - - [Jupyter Notebook](http://nbviewer.jupyter.org/url/norvig.com/ipython/TSP.ipynb) - - Pages 1048 - 1140 in CLRS if you have it. +- ### Caches + - [ ] LRU cache: + - [ ] [The Magic of LRU Cache (100 Days of Google Dev) (video)](https://www.youtube.com/watch?v=R5ON3iwx78M) + - [ ] [Implementing LRU (video)](https://www.youtube.com/watch?v=bq6N7Ym81iI) + - [ ] [LeetCode - 146 LRU Cache (C++) (video)](https://www.youtube.com/watch?v=8-FZRAjR7qU) + - [ ] CPU cache: + - [ ] [MIT 6.004 L15: The Memory Hierarchy (video)](https://www.youtube.com/watch?v=vjYF_fAZI5E&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-&index=24) + - [ ] [MIT 6.004 L16: Cache Issues (video)](https://www.youtube.com/watch?v=ajgC3-pyGlk&index=25&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-) -* ### Caches +- ### Processes and Threads + - [ ] Computer Science 162 - Operating Systems (25 videos): + - for processes and threads see videos 1-11 + - [Operating Systems and System Programming (video)](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iBDyz-ba4yDskqMDY6A1w_c) + - [What Is The Difference Between A Process And A Thread?](https://www.quora.com/What-is-the-difference-between-a-process-and-a-thread) + - Covers: + - Processes, Threads, Concurrency issues + - difference between processes and threads + - processes + - threads + - locks + - mutexes + - semaphores + - monitors + - how they work + - deadlock + - livelock + - CPU activity, interrupts, context switching + - Modern concurrency constructs with multicore processors + - [Paging, segmentation and virtual memory (video)](https://www.youtube.com/watch?v=LKe7xK0bF7o&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=2) + - [Interrupts (video)](https://www.youtube.com/watch?v=uFKi2-J-6II&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=3) + - [Scheduling (video)](https://www.youtube.com/watch?v=-Gu5mYdKbu4&index=4&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8) + - Process resource needs (memory: code, static storage, stack, heap, and also file descriptors, i/o) + - Thread resource needs (shares above (minus stack) with other threads in the same process but each has its own pc, stack counter, registers, and stack) + - Forking is really copy on write (read-only) until the new process writes to memory, then it does a full copy. + - Context switching + - How context switching is initiated by the operating system and underlying hardware + - [ ] [threads in C++ (series - 10 videos)](https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M) + - [ ] concurrency in Python (videos): + - [ ] [Short series on threads](https://www.youtube.com/playlist?list=PL1H1sBF1VAKVMONJWJkmUh6_p8g4F2oy1) + - [ ] [Python Threads](https://www.youtube.com/watch?v=Bs7vPNbB9JM) + - [ ] [Understanding the Python GIL (2010)](https://www.youtube.com/watch?v=Obt-vMVdM8s) + - [reference](http://www.dabeaz.com/GIL) + - [ ] [David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015](https://www.youtube.com/watch?v=MCs5OvhV9S4) + - [ ] [Keynote David Beazley - Topics of Interest (Python Asyncio)](https://www.youtube.com/watch?v=ZzfHjytDceU) + - [ ] [Mutex in Python](https://www.youtube.com/watch?v=0zaPs8OtyKY) - - [ ] LRU cache: - - [ ] [The Magic of LRU Cache (100 Days of Google Dev) (video)](https://www.youtube.com/watch?v=R5ON3iwx78M) - - [ ] [Implementing LRU (video)](https://www.youtube.com/watch?v=bq6N7Ym81iI) - - [ ] [LeetCode - 146 LRU Cache (C++) (video)](https://www.youtube.com/watch?v=8-FZRAjR7qU) - - [ ] CPU cache: - - [ ] [MIT 6.004 L15: The Memory Hierarchy (video)](https://www.youtube.com/watch?v=vjYF_fAZI5E&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-&index=24) - - [ ] [MIT 6.004 L16: Cache Issues (video)](https://www.youtube.com/watch?v=ajgC3-pyGlk&index=25&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-) +- ### Testing + - To cover: + - how unit testing works + - what are mock objects + - what is integration testing + - what is dependency injection + - [ ] [Agile Software Testing with James Bach (video)](https://www.youtube.com/watch?v=SAhJf36_u5U) + - [ ] [Open Lecture by James Bach on Software Testing (video)](https://www.youtube.com/watch?v=ILkT_HV9DVU) + - [ ] [Steve Freeman - Test-Driven Development (that’s not what we meant) (video)](https://vimeo.com/83960706) + - [slides](http://gotocon.com/dl/goto-berlin-2013/slides/SteveFreeman_TestDrivenDevelopmentThatsNotWhatWeMeant.pdf) + - [ ] Dependency injection: + - [ ] [video](https://www.youtube.com/watch?v=IKD2-MAkXyQ) + - [ ] [Tao Of Testing](http://jasonpolites.github.io/tao-of-testing/ch3-1.1.html) + - [ ] [How to write tests](http://jasonpolites.github.io/tao-of-testing/ch4-1.1.html) -* ### Processes and Threads +- ### Scheduling + - in an OS, how it works + - can be gleaned from Operating System videos - - [ ] Computer Science 162 - Operating Systems (25 videos): - - for processes and threads see videos 1-11 - - [Operating Systems and System Programming (video)](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iBDyz-ba4yDskqMDY6A1w_c) - - [What Is The Difference Between A Process And A Thread?](https://www.quora.com/What-is-the-difference-between-a-process-and-a-thread) - - Covers: - - Processes, Threads, Concurrency issues - - difference between processes and threads - - processes - - threads - - locks - - mutexes - - semaphores - - monitors - - how they work - - deadlock - - livelock - - CPU activity, interrupts, context switching - - Modern concurrency constructs with multicore processors - - [Paging, segmentation and virtual memory (video)](https://www.youtube.com/watch?v=LKe7xK0bF7o&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=2) - - [Interrupts (video)](https://www.youtube.com/watch?v=uFKi2-J-6II&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=3) - - Process resource needs (memory: code, static storage, stack, heap, and also file descriptors, i/o) - - Thread resource needs (shares above (minus stack) with other threads in the same process but each has its own pc, stack counter, registers, and stack) - - Forking is really copy on write (read-only) until the new process writes to memory, then it does a full copy. - - Context switching - - How context switching is initiated by the operating system and underlying hardware - - [ ] [threads in C++ (series - 10 videos)](https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M) - - [ ] concurrency in Python (videos): - - [ ] [Short series on threads](https://www.youtube.com/playlist?list=PL1H1sBF1VAKVMONJWJkmUh6_p8g4F2oy1) - - [ ] [Python Threads](https://www.youtube.com/watch?v=Bs7vPNbB9JM) - - [ ] [Understanding the Python GIL (2010)](https://www.youtube.com/watch?v=Obt-vMVdM8s) - - [reference](http://www.dabeaz.com/GIL) - - [ ] [David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015](https://www.youtube.com/watch?v=MCs5OvhV9S4) - - [ ] [Keynote David Beazley - Topics of Interest (Python Asyncio)](https://www.youtube.com/watch?v=ZzfHjytDceU) - - [ ] [Mutex in Python](https://www.youtube.com/watch?v=0zaPs8OtyKY) +- ### String searching & manipulations + - [ ] [Sedgewick - Suffix Arrays (video)](https://www.coursera.org/learn/algorithms-part2/lecture/TH18W/suffix-arrays) + - [ ] [Sedgewick - Substring Search (videos)](https://www.coursera.org/learn/algorithms-part2/home/week/4) + - [ ] [1. Introduction to Substring Search](https://www.coursera.org/learn/algorithms-part2/lecture/n3ZpG/introduction-to-substring-search) + - [ ] [2. Brute-Force Substring Search](https://www.coursera.org/learn/algorithms-part2/lecture/2Kn5i/brute-force-substring-search) + - [ ] [3. Knuth-Morris Pratt](https://www.coursera.org/learn/algorithms-part2/lecture/TAtDr/knuth-morris-pratt) + - [ ] [4. Boyer-Moore](https://www.coursera.org/learn/algorithms-part2/lecture/CYxOT/boyer-moore) + - [ ] [5. Rabin-Karp](https://www.coursera.org/learn/algorithms-part2/lecture/3KiqT/rabin-karp) + - [ ] [Search pattern in text (video)](https://www.coursera.org/learn/data-structures/lecture/tAfHI/search-pattern-in-text) -* ### Testing + If you need more detail on this subject, see "String Matching" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects) - - To cover: - - how unit testing works - - what are mock objects - - what is integration testing - - what is dependency injection - - [ ] [Agile Software Testing with James Bach (video)](https://www.youtube.com/watch?v=SAhJf36_u5U) - - [ ] [Open Lecture by James Bach on Software Testing (video)](https://www.youtube.com/watch?v=ILkT_HV9DVU) - - [ ] [Steve Freeman - Test-Driven Development (that’s not what we meant) (video)](https://vimeo.com/83960706) - - [slides](http://gotocon.com/dl/goto-berlin-2013/slides/SteveFreeman_TestDrivenDevelopmentThatsNotWhatWeMeant.pdf) - - [ ] Dependency injection: - - [ ] [video](https://www.youtube.com/watch?v=IKD2-MAkXyQ) - - [ ] [Tao Of Testing](http://jasonpolites.github.io/tao-of-testing/ch3-1.1.html) - - [ ] [How to write tests](http://jasonpolites.github.io/tao-of-testing/ch4-1.1.html) +- ### Tries + - Note there are different kinds of tries. Some have prefixes, some don't, and some use string instead of bits + to track the path. + - I read through code, but will not implement. + - [ ] [Sedgewick - Tries (3 videos)](https://www.coursera.org/learn/algorithms-part2/home/week/4) + - [ ] [1. R Way Tries](https://www.coursera.org/learn/algorithms-part2/lecture/CPVdr/r-way-tries) + - [ ] [2. Ternary Search Tries](https://www.coursera.org/learn/algorithms-part2/lecture/yQM8K/ternary-search-tries) + - [ ] [3. Character Based Operations](https://www.coursera.org/learn/algorithms-part2/lecture/jwNmV/character-based-operations) + - [ ] [Notes on Data Structures and Programming Techniques](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Tries) + - [ ] Short course videos: + - [ ] [Introduction To Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries) + - [ ] [Performance Of Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries) + - [ ] [Implementing A Trie (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie) + - [ ] [The Trie: A Neglected Data Structure](https://www.toptal.com/java/the-trie-a-neglected-data-structure) + - [ ] [TopCoder - Using Tries](https://www.topcoder.com/community/competitive-programming/tutorials/using-tries/) + - [ ] [Stanford Lecture (real world use case) (video)](https://www.youtube.com/watch?v=TJ8SkcUSdbU) + - [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through) (video)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf) -* ### Scheduling +- ### Floating Point Numbers + - [ ] simple 8-bit: [Representation of Floating Point Numbers - 1 (video - there is an error in calculations - see video description)](https://www.youtube.com/watch?v=ji3SfClm8TU) + - [ ] 32 bit: [IEEE754 32-bit floating point binary (video)](https://www.youtube.com/watch?v=50ZYcZebIec) - - in an OS, how it works - - can be gleaned from Operating System videos +- ### Unicode + - [ ] [The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets]( http://www.joelonsoftware.com/articles/Unicode.html) + - [ ] [What Every Programmer Absolutely, Positively Needs To Know About Encodings And Character Sets To Work With Text](http://kunststube.net/encoding/) -* ### String searching & manipulations +- ### Endianness + - [ ] [Big And Little Endian](https://web.archive.org/web/20180107141940/http://www.cs.umd.edu:80/class/sum2003/cmsc311/Notes/Data/endian.html) + - [ ] [Big Endian Vs Little Endian (video)](https://www.youtube.com/watch?v=JrNF0KRAlyo) + - [ ] [Big And Little Endian Inside/Out (video)](https://www.youtube.com/watch?v=oBSuXP-1Tc0) + - Very technical talk for kernel devs. Don't worry if most is over your head. + - The first half is enough. - - [ ] [Sedgewick - Suffix Arrays (video)](https://www.coursera.org/learn/algorithms-part2/lecture/TH18W/suffix-arrays) - - [ ] [Sedgewick - Substring Search (videos)](https://www.coursera.org/learn/algorithms-part2/home/week/4) - - [ ] [1. Introduction to Substring Search](https://www.coursera.org/learn/algorithms-part2/lecture/n3ZpG/introduction-to-substring-search) - - [ ] [2. Brute-Force Substring Search](https://www.coursera.org/learn/algorithms-part2/lecture/2Kn5i/brute-force-substring-search) - - [ ] [3. Knuth-Morris Pratt](https://www.coursera.org/learn/algorithms-part2/lecture/TAtDr/knuth-morris-pratt) - - [ ] [4. Boyer-Moore](https://www.coursera.org/learn/algorithms-part2/lecture/CYxOT/boyer-moore) - - [ ] [5. Rabin-Karp](https://www.coursera.org/learn/algorithms-part2/lecture/3KiqT/rabin-karp) - - [ ] [Search pattern in text (video)](https://www.coursera.org/learn/data-structures/lecture/tAfHI/search-pattern-in-text) - - If you need more detail on this subject, see "String Matching" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects) - -* ### Tries - - - Note there are different kinds of tries. Some have prefixes, some don't, and some use string instead of bits - to track the path. - - I read through code, but will not implement. - - [ ] [Sedgewick - Tries (3 videos)](https://www.coursera.org/learn/algorithms-part2/home/week/4) - - [ ] [1. R Way Tries](https://www.coursera.org/learn/algorithms-part2/lecture/CPVdr/r-way-tries) - - [ ] [2. Ternary Search Tries](https://www.coursera.org/learn/algorithms-part2/lecture/yQM8K/ternary-search-tries) - - [ ] [3. Character Based Operations](https://www.coursera.org/learn/algorithms-part2/lecture/jwNmV/character-based-operations) - - [ ] [Notes on Data Structures and Programming Techniques](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Tries) - - [ ] Short course videos: - - [ ] [Introduction To Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries) - - [ ] [Performance Of Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries) - - [ ] [Implementing A Trie (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie) - - [ ] [The Trie: A Neglected Data Structure](https://www.toptal.com/java/the-trie-a-neglected-data-structure) - - [ ] [TopCoder - Using Tries](https://www.topcoder.com/community/competitive-programming/tutorials/using-tries/) - - [ ] [Stanford Lecture (real world use case) (video)](https://www.youtube.com/watch?v=TJ8SkcUSdbU) - - [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through) (video)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf) - -* ### Floating Point Numbers - - - [ ] simple 8-bit: [Representation of Floating Point Numbers - 1 (video - there is an error in calculations - see video description)](https://www.youtube.com/watch?v=ji3SfClm8TU) - - [ ] 32 bit: [IEEE754 32-bit floating point binary (video)](https://www.youtube.com/watch?v=50ZYcZebIec) - -* ### Unicode - - - [ ] [The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets](http://www.joelonsoftware.com/articles/Unicode.html) - - [ ] [What Every Programmer Absolutely, Positively Needs To Know About Encodings And Character Sets To Work With Text](http://kunststube.net/encoding/) - -* ### Endianness - - - [ ] [Big And Little Endian](https://web.archive.org/web/20180107141940/http://www.cs.umd.edu:80/class/sum2003/cmsc311/Notes/Data/endian.html) - - [ ] [Big Endian Vs Little Endian (video)](https://www.youtube.com/watch?v=JrNF0KRAlyo) - - [ ] [Big And Little Endian Inside/Out (video)](https://www.youtube.com/watch?v=oBSuXP-1Tc0) - - Very technical talk for kernel devs. Don't worry if most is over your head. - - The first half is enough. - -* ### Networking - - **if you have networking experience or want to be a reliability engineer or operations engineer, expect questions** - - otherwise, this is just good to know - - [ ] [Khan Academy](https://www.khanacademy.org/computing/computer-science/internet-intro) - - [ ] [UDP and TCP: Comparison of Transport Protocols (video)](https://www.youtube.com/watch?v=Vdc8TCESIg8) - - [ ] [TCP/IP and the OSI Model Explained! (video)](https://www.youtube.com/watch?v=e5DEVa9eSN0) - - [ ] [Packet Transmission across the Internet. Networking & TCP/IP tutorial. (video)](https://www.youtube.com/watch?v=nomyRJehhnM) - - [ ] [HTTP (video)](https://www.youtube.com/watch?v=WGJrLqtX7As) - - [ ] [SSL and HTTPS (video)](https://www.youtube.com/watch?v=S2iBR2ZlZf0) - - [ ] [SSL/TLS (video)](https://www.youtube.com/watch?v=Rp3iZUvXWlM) - - [ ] [HTTP 2.0 (video)](https://www.youtube.com/watch?v=E9FxNzv1Tr8) - - [ ] [Video Series (21 videos) (video)](https://www.youtube.com/playlist?list=PLEbnTDJUr_IegfoqO4iPnPYQui46QqT0j) - - [ ] [Subnetting Demystified - Part 5 CIDR Notation (video)](https://www.youtube.com/watch?v=t5xYI0jzOf4) - - [ ] Sockets: - - [ ] [Java - Sockets - Introduction (video)](https://www.youtube.com/watch?v=6G_W54zuadg&t=6s) - - [ ] [Socket Programming (video)](https://www.youtube.com/watch?v=G75vN2mnJeQ) +- ### Networking + - **if you have networking experience or want to be a reliability engineer or operations engineer, expect questions** + - otherwise, this is just good to know + - [ ] [Khan Academy](https://www.khanacademy.org/computing/computer-science/internet-intro) + - [ ] [UDP and TCP: Comparison of Transport Protocols (video)](https://www.youtube.com/watch?v=Vdc8TCESIg8) + - [ ] [TCP/IP and the OSI Model Explained! (video)](https://www.youtube.com/watch?v=e5DEVa9eSN0) + - [ ] [Packet Transmission across the Internet. Networking & TCP/IP tutorial. (video)](https://www.youtube.com/watch?v=nomyRJehhnM) + - [ ] [HTTP (video)](https://www.youtube.com/watch?v=WGJrLqtX7As) + - [ ] [SSL and HTTPS (video)](https://www.youtube.com/watch?v=S2iBR2ZlZf0) + - [ ] [SSL/TLS (video)](https://www.youtube.com/watch?v=Rp3iZUvXWlM) + - [ ] [HTTP 2.0 (video)](https://www.youtube.com/watch?v=E9FxNzv1Tr8) + - [ ] [Video Series (21 videos) (video)](https://www.youtube.com/playlist?list=PLEbnTDJUr_IegfoqO4iPnPYQui46QqT0j) + - [ ] [Subnetting Demystified - Part 5 CIDR Notation (video)](https://www.youtube.com/watch?v=t5xYI0jzOf4) + - [ ] Sockets: + - [ ] [Java - Sockets - Introduction (video)](https://www.youtube.com/watch?v=6G_W54zuadg&t=6s) + - [ ] [Socket Programming (video)](https://www.youtube.com/watch?v=G75vN2mnJeQ) ## System Design, Scalability, Data Handling **You can expect system design questions if you have 4+ years of experience.** - Scalability and System Design are very large topics with many topics and resources, since - there is a lot to consider when designing a software/hardware system that can scale. - Expect to spend quite a bit of time on this. + there is a lot to consider when designing a software/hardware system that can scale. + Expect to spend quite a bit of time on this. - Considerations: - - scalability - - Distill large data sets to single values - - Transform one data set to another - - Handling obscenely large amounts of data - - system design - - features sets - - interfaces - - class hierarchies - - designing a system under certain constraints - - simplicity and robustness - - tradeoffs - - performance analysis and optimization + - scalability + - Distill large data sets to single values + - Transform one data set to another + - Handling obscenely large amounts of data + - system design + - features sets + - interfaces + - class hierarchies + - designing a system under certain constraints + - simplicity and robustness + - tradeoffs + - performance analysis and optimization - [ ] **START HERE**: [The System Design Primer](https://github.com/donnemartin/system-design-primer) - [ ] [System Design from HiredInTech](http://www.hiredintech.com/system-design/) - [ ] [How Do I Prepare To Answer Design Questions In A Technical Inverview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023) @@ -1164,99 +1132,99 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] [Transactions Across Datacenters (video)](https://www.youtube.com/watch?v=srOgpXECblk) - [ ] [A plain English introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem/) - [ ] Consensus Algorithms: - - [ ] Paxos - [Paxos Agreement - Computerphile (video)](https://www.youtube.com/watch?v=s8JqcZtvnsM) - - [ ] Raft - [An Introduction to the Raft Distributed Consensus Algorithm (video)](https://www.youtube.com/watch?v=P9Ydif5_qvE) - - [ ] [Easy-to-read paper](https://raft.github.io/) - - [ ] [Infographic](http://thesecretlivesofdata.com/raft/) + - [ ] Paxos - [Paxos Agreement - Computerphile (video)](https://www.youtube.com/watch?v=s8JqcZtvnsM) + - [ ] Raft - [An Introduction to the Raft Distributed Consensus Algorithm (video)](https://www.youtube.com/watch?v=P9Ydif5_qvE) + - [ ] [Easy-to-read paper](https://raft.github.io/) + - [ ] [Infographic](http://thesecretlivesofdata.com/raft/) - [ ] [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html) - [ ] [NoSQL Patterns](http://horicky.blogspot.com/2009/11/nosql-patterns.html) - [ ] Scalability: - - You don't need all of these. Just pick a few that interest you. - - [ ] [Great overview (video)](https://www.youtube.com/watch?v=-W9F__D3oY4) - - [ ] Short series: - - [Clones](http://www.lecloud.net/post/7295452622/scalability-for-dummies-part-1-clones) - - [Database](http://www.lecloud.net/post/7994751381/scalability-for-dummies-part-2-database) - - [Cache](http://www.lecloud.net/post/9246290032/scalability-for-dummies-part-3-cache) - - [Asynchronism](http://www.lecloud.net/post/9699762917/scalability-for-dummies-part-4-asynchronism) - - [ ] [Scalable Web Architecture and Distributed Systems](http://www.aosabook.org/en/distsys.html) - - [ ] [Fallacies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/fallacies.pdf) - - [ ] [Pragmatic Programming Techniques](http://horicky.blogspot.com/2010/10/scalable-system-design-patterns.html) - - [extra: Google Pregel Graph Processing](http://horicky.blogspot.com/2010/07/google-pregel-graph-processing.html) - - [ ] [Jeff Dean - Building Software Systems At Google and Lessons Learned (video)](https://www.youtube.com/watch?v=modXC5IWTJI) - - [ ] [Introduction to Architecting Systems for Scale](http://lethain.com/introduction-to-architecting-systems-for-scale/) - - [ ] [Scaling mobile games to a global audience using App Engine and Cloud Datastore (video)](https://www.youtube.com/watch?v=9nWyWwY2Onc) - - [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (video)](https://www.youtube.com/watch?v=H4vMcD7zKM0) - - [ ] [The Importance of Algorithms](https://www.topcoder.com/community/competitive-programming/tutorials/the-importance-of-algorithms/) - - [ ] [Sharding](http://highscalability.com/blog/2009/8/6/an-unorthodox-approach-to-database-design-the-coming-of-the.html) - - [ ] [Scale at Facebook (2012), "Building for a Billion Users" (video)](https://www.youtube.com/watch?v=oodS71YtkGU) - - [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(video)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4) - - [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html) - - [video](https://www.youtube.com/watch?v=G-lGCC4KKok) - - [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html) - - [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/) - - [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (video)](https://www.youtube.com/watch?v=3vV4YiqKm1o) - - [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/) - - [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/) - - [ ] [Asyncio Tarantool Queue, Get In The Queue](http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html) - - [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html) - - [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture](http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html) - - [ ] [Spanner](http://highscalability.com/blog/2012/9/24/google-spanners-most-surprising-revelation-nosql-is-out-and.html) - - [ ] [Machine Learning Driven Programming: A New Programming For A New World](http://highscalability.com/blog/2016/7/6/machine-learning-driven-programming-a-new-programming-for-a.html) - - [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html) - - [ ] [A Patreon Architecture Short](http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html) - - [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html) - - [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html) - - [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html) - - [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html) - - [ ] [How Does The Use Of Docker Effect Latency?](http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html) - - [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html) - - [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it) - - [ ] [Serverless (very long, just need the gist)](http://martinfowler.com/articles/serverless.html) - - [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances) - - [ ] [Cinchcast Architecture - Producing 1,500 Hours Of Audio Every Day](http://highscalability.com/blog/2012/7/16/cinchcast-architecture-producing-1500-hours-of-audio-every-d.html) - - [ ] [Justin.Tv's Live Video Broadcasting Architecture](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html) - - [ ] [Playfish's Social Gaming Architecture - 50 Million Monthly Users And Growing](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html) - - [ ] [TripAdvisor Architecture - 40M Visitors, 200M Dynamic Page Views, 30TB Data](http://highscalability.com/blog/2011/6/27/tripadvisor-architecture-40m-visitors-200m-dynamic-page-view.html) - - [ ] [PlentyOfFish Architecture](http://highscalability.com/plentyoffish-architecture) - - [ ] [Salesforce Architecture - How They Handle 1.3 Billion Transactions A Day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html) - - [ ] [ESPN's Architecture At Scale - Operating At 100,000 Duh Nuh Nuhs Per Second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html) - - [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together - - [ ] Twitter: - - [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (video)](https://www.youtube.com/watch?v=5cKTP36HVgI) - - [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability) - - For even more, see "Mining Massive Datasets" video series in the [Video Series](#video-series) section. + - You don't need all of these. Just pick a few that interest you. + - [ ] [Great overview (video)](https://www.youtube.com/watch?v=-W9F__D3oY4) + - [ ] Short series: + - [Clones](http://www.lecloud.net/post/7295452622/scalability-for-dummies-part-1-clones) + - [Database](http://www.lecloud.net/post/7994751381/scalability-for-dummies-part-2-database) + - [Cache](http://www.lecloud.net/post/9246290032/scalability-for-dummies-part-3-cache) + - [Asynchronism](http://www.lecloud.net/post/9699762917/scalability-for-dummies-part-4-asynchronism) + - [ ] [Scalable Web Architecture and Distributed Systems](http://www.aosabook.org/en/distsys.html) + - [ ] [Fallacies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/fallacies.pdf) + - [ ] [Pragmatic Programming Techniques](http://horicky.blogspot.com/2010/10/scalable-system-design-patterns.html) + - [extra: Google Pregel Graph Processing](http://horicky.blogspot.com/2010/07/google-pregel-graph-processing.html) + - [ ] [Jeff Dean - Building Software Systems At Google and Lessons Learned (video)](https://www.youtube.com/watch?v=modXC5IWTJI) + - [ ] [Introduction to Architecting Systems for Scale](http://lethain.com/introduction-to-architecting-systems-for-scale/) + - [ ] [Scaling mobile games to a global audience using App Engine and Cloud Datastore (video)](https://www.youtube.com/watch?v=9nWyWwY2Onc) + - [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (video)](https://www.youtube.com/watch?v=H4vMcD7zKM0) + - [ ] [The Importance of Algorithms](https://www.topcoder.com/community/competitive-programming/tutorials/the-importance-of-algorithms/) + - [ ] [Sharding](http://highscalability.com/blog/2009/8/6/an-unorthodox-approach-to-database-design-the-coming-of-the.html) + - [ ] [Scale at Facebook (2012), "Building for a Billion Users" (video)](https://www.youtube.com/watch?v=oodS71YtkGU) + - [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(video)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4) + - [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html) + - [video](https://www.youtube.com/watch?v=G-lGCC4KKok) + - [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html) + - [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/) + - [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (video)](https://www.youtube.com/watch?v=3vV4YiqKm1o) + - [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/) + - [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/) + - [ ] [Asyncio Tarantool Queue, Get In The Queue](http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html) + - [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html) + - [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture]( http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html) + - [ ] [Spanner](http://highscalability.com/blog/2012/9/24/google-spanners-most-surprising-revelation-nosql-is-out-and.html) + - [ ] [Machine Learning Driven Programming: A New Programming For A New World](http://highscalability.com/blog/2016/7/6/machine-learning-driven-programming-a-new-programming-for-a.html) + - [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html) + - [ ] [A Patreon Architecture Short](http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html) + - [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html) + - [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html) + - [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html) + - [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html) + - [ ] [How Does The Use Of Docker Effect Latency?](http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html) + - [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html) + - [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it) + - [ ] [Serverless (very long, just need the gist)](http://martinfowler.com/articles/serverless.html) + - [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances) + - [ ] [Cinchcast Architecture - Producing 1,500 Hours Of Audio Every Day](http://highscalability.com/blog/2012/7/16/cinchcast-architecture-producing-1500-hours-of-audio-every-d.html) + - [ ] [Justin.Tv's Live Video Broadcasting Architecture](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html) + - [ ] [Playfish's Social Gaming Architecture - 50 Million Monthly Users And Growing](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html) + - [ ] [TripAdvisor Architecture - 40M Visitors, 200M Dynamic Page Views, 30TB Data](http://highscalability.com/blog/2011/6/27/tripadvisor-architecture-40m-visitors-200m-dynamic-page-view.html) + - [ ] [PlentyOfFish Architecture](http://highscalability.com/plentyoffish-architecture) + - [ ] [Salesforce Architecture - How They Handle 1.3 Billion Transactions A Day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html) + - [ ] [ESPN's Architecture At Scale - Operating At 100,000 Duh Nuh Nuhs Per Second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html) + - [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together + - [ ] Twitter: + - [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (video)](https://www.youtube.com/watch?v=5cKTP36HVgI) + - [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability) + - For even more, see "Mining Massive Datasets" video series in the [Video Series](#video-series) section. - [ ] Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world: - - review: [The System Design Primer](https://github.com/donnemartin/system-design-primer) - - [System Design from HiredInTech](http://www.hiredintech.com/system-design/) - - [cheat sheet](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/system-design.pdf) - - flow: - 1. Understand the problem and scope: - - define the use cases, with interviewer's help - - suggest additional features - - remove items that interviewer deems out of scope - - assume high availability is required, add as a use case - 2. Think about constraints: - - ask how many requests per month - - ask how many requests per second (they may volunteer it or make you do the math) - - estimate reads vs. writes percentage - - keep 80/20 rule in mind when estimating - - how much data written per second - - total storage required over 5 years - - how much data read per second - 3. Abstract design: - - layers (service, data, caching) - - infrastructure: load balancing, messaging - - rough overview of any key algorithm that drives the service - - consider bottlenecks and determine solutions - - Exercises: - - [Design a CDN network: old article](http://repository.cmu.edu/cgi/viewcontent.cgi?article=2112&context=compsci) - - [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake) - - [Design an online multiplayer card game](http://www.indieflashblog.com/how-to-create-an-asynchronous-multiplayer-game.html) - - [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis) - - [Design a picture sharing system](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html) - - [Design a recommendation system](http://ijcai13.org/files/tutorial_slides/td3.pdf) - - [Design a URL-shortener system: copied from above](http://www.hiredintech.com/system-design/the-system-design-process/) - - [Design a cache system](https://www.adayinthelifeof.nl/2011/02/06/memcache-internals/) + - review: [The System Design Primer](https://github.com/donnemartin/system-design-primer) + - [System Design from HiredInTech](http://www.hiredintech.com/system-design/) + - [cheat sheet](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/system-design.pdf) + - flow: + 1. Understand the problem and scope: + - define the use cases, with interviewer's help + - suggest additional features + - remove items that interviewer deems out of scope + - assume high availability is required, add as a use case + 2. Think about constraints: + - ask how many requests per month + - ask how many requests per second (they may volunteer it or make you do the math) + - estimate reads vs. writes percentage + - keep 80/20 rule in mind when estimating + - how much data written per second + - total storage required over 5 years + - how much data read per second + 3. Abstract design: + - layers (service, data, caching) + - infrastructure: load balancing, messaging + - rough overview of any key algorithm that drives the service + - consider bottlenecks and determine solutions + - Exercises: + - [Design a CDN network: old article](http://repository.cmu.edu/cgi/viewcontent.cgi?article=2112&context=compsci) + - [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake) + - [Design an online multiplayer card game](http://www.indieflashblog.com/how-to-create-an-asynchronous-multiplayer-game.html) + - [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis) + - [Design a picture sharing system](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html) + - [Design a recommendation system](http://ijcai13.org/files/tutorial_slides/td3.pdf) + - [Design a URL-shortener system: copied from above](http://www.hiredintech.com/system-design/the-system-design-process/) + - [Design a cache system](https://www.adayinthelifeof.nl/2011/02/06/memcache-internals/) --- @@ -1266,9 +1234,9 @@ Graphs can be used to represent many problems in computer science, so this secti It's nice if you want a refresher often. - [ ] Series of 2-3 minutes short subject videos (23 videos) - - [Videos](https://www.youtube.com/watch?v=r4r1DZcx1cM&list=PLmVb1OknmNJuC5POdcDv5oCS7_OUkDgpj&index=22) + - [Videos](https://www.youtube.com/watch?v=r4r1DZcx1cM&list=PLmVb1OknmNJuC5POdcDv5oCS7_OUkDgpj&index=22) - [ ] Series of 2-5 minutes short subject videos - Michael Sambol (18 videos): - - [Videos](https://www.youtube.com/channel/UCzDJwLWoYCUQowF_nG3m5OQ) + - [Videos](https://www.youtube.com/channel/UCzDJwLWoYCUQowF_nG3m5OQ) - [ ] [Sedgewick Videos - Algorithms I](https://www.coursera.org/learn/algorithms-part1) - [ ] [Sedgewick Videos - Algorithms II](https://www.coursera.org/learn/algorithms-part2) @@ -1281,7 +1249,6 @@ Now that you know all the computer science topics above, it's time to practice a **Coding question practice is not about memorizing answers to programming problems.** Why you need to practice doing programming problems: - - problem recognition, and where the right data structures and algorithms fit in - gathering requirements for the problem - talking your way through the problem like you will in the interview @@ -1295,7 +1262,7 @@ interview books, too, but I found this outstanding: No whiteboard at home? That makes sense. I'm a weirdo and have a big whiteboard. Instead of a whiteboard, pick up a large drawing pad from an art store. You can sit on the couch and practice. This is my "sofa whiteboard". -I added the pen in the photo for scale. If you use a pen, you'll wish you could erase. Gets messy quick. I use a pencil +I added the pen in the photo for scale. If you use a pen, you'll wish you could erase. Gets messy quick. I use a pencil and eraser. ![my sofa whiteboard](https://d3j2pkmjtin6ou.cloudfront.net/art_board_sm_2.jpg) @@ -1310,12 +1277,13 @@ Supplemental: **Read and Do Programming Problems (in this order):** - [ ] [Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition](http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html) - - answers in C, C++ and Java + - answers in C, C++ and Java - [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/) - - answers in Java + - answers in Java See [Book List above](#book-list) + ## Coding exercises/challenges Once you've learned your brains out, put those brains to work. @@ -1325,12 +1293,10 @@ Take coding challenges every day, as many as you can. - [How to Dissect a Topcoder Problem Statement](https://www.topcoder.com/community/competitive-programming/tutorials/how-to-dissect-a-topcoder-problem-statement/) Coding Interview Question Videos: - - [IDeserve (88 videos)](https://www.youtube.com/watch?v=NBcqBddFbZw&list=PLamzFoFxwoNjPfxzaWqs7cZGsPYy0x_gI) - [Tushar Roy (5 playlists)](https://www.youtube.com/user/tusharroy2525/playlists?shelf_id=2&view=50&sort=dd) Challenge sites: - - [LeetCode](https://leetcode.com/) - [TopCoder](https://www.topcoder.com/) - [Project Euler (math-focused)](https://projecteuler.net/index.php?section=problems) @@ -1345,25 +1311,25 @@ Challenge sites: - [Codechef](https://www.codechef.com/) Challenge repos: - - [Interactive Coding Interview Challenges in Python](https://github.com/donnemartin/interactive-coding-challenges) Mock Interviews: - - [Gainlo.co: Mock interviewers from big companies](http://www.gainlo.co/) - I used this and it helped me relax for the phone screen and on-site interview. - [Pramp: Mock interviews from/with peers](https://www.pramp.com/) - peer-to-peer model of practice interviews - [Refdash: Mock interviews and expedited interviews](https://refdash.com/) - also help candidates fast track by skipping multiple interviews with tech companies. + ## Once you're closer to the interview - Cracking The Coding Interview Set 2 (videos): - - [Cracking The Code Interview](https://www.youtube.com/watch?v=4NIb9l3imAo) - - [Cracking the Coding Interview - Fullstack Speaker Series](https://www.youtube.com/watch?v=Eg5-tdAwclo) + - [Cracking The Code Interview](https://www.youtube.com/watch?v=4NIb9l3imAo) + - [Cracking the Coding Interview - Fullstack Speaker Series](https://www.youtube.com/watch?v=Eg5-tdAwclo) ## Your Resume - See Resume prep items in Cracking The Coding Interview and back of Programming Interviews Exposed + ## Be thinking of for when the interview comes Think of about 20 interview questions you'll get, along with the lines of the items below. Have 2-3 answers for each. @@ -1424,421 +1390,389 @@ You're never really done. These are here so you can dive into a topic you find interesting. - [The Unix Programming Environment](https://www.amazon.com/dp/013937681X) - - an oldie but a goodie + - an oldie but a goodie - [The Linux Command Line: A Complete Introduction](https://www.amazon.com/dp/1593273894/) - - a modern option + - a modern option - [TCP/IP Illustrated Series](https://en.wikipedia.org/wiki/TCP/IP_Illustrated) - [Head First Design Patterns](https://www.amazon.com/gp/product/0596007124/) - - a gentle introduction to design patterns + - a gentle introduction to design patterns - [Design Patterns: Elements of Reusable Object-Oriente​d Software](https://www.amazon.com/Design-Patterns-Elements-Reusable-Object-Oriented/dp/0201633612) - - aka the "Gang Of Four" book, or GOF - - the canonical design patterns book + - aka the "Gang Of Four" book, or GOF + - the canonical design patterns book - [UNIX and Linux System Administration Handbook, 5th Edition](https://www.amazon.com/UNIX-Linux-System-Administration-Handbook/dp/0134277554/) - [Algorithm Design Manual](http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202) (Skiena) - - As a review and problem recognition - - The algorithm catalog portion is well beyond the scope of difficulty you'll get in an interview. - - This book has 2 parts: - - class textbook on data structures and algorithms - - pros: - - is a good review as any algorithms textbook would be - - nice stories from his experiences solving problems in industry and academia - - code examples in C - - cons: - - can be as dense or impenetrable as CLRS, and in some cases, CLRS may be a better alternative for some subjects - - chapters 7, 8, 9 can be painful to try to follow, as some items are not explained well or require more brain than I have - - don't get me wrong: I like Skiena, his teaching style, and mannerisms, but I may not be Stony Brook material. - - algorithm catalog: - - this is the real reason you buy this book. - - about to get to this part. Will update here once I've made my way through it. - - Can rent it on kindle - - Answers: - - [Solutions]() - - [Solutions](http://blog.panictank.net/category/algorithmndesignmanualsolutions/page/2/) - - [Errata](http://www3.cs.stonybrook.edu/~skiena/algorist/book/errata) + - As a review and problem recognition + - The algorithm catalog portion is well beyond the scope of difficulty you'll get in an interview. + - This book has 2 parts: + - class textbook on data structures and algorithms + - pros: + - is a good review as any algorithms textbook would be + - nice stories from his experiences solving problems in industry and academia + - code examples in C + - cons: + - can be as dense or impenetrable as CLRS, and in some cases, CLRS may be a better alternative for some subjects + - chapters 7, 8, 9 can be painful to try to follow, as some items are not explained well or require more brain than I have + - don't get me wrong: I like Skiena, his teaching style, and mannerisms, but I may not be Stony Brook material. + - algorithm catalog: + - this is the real reason you buy this book. + - about to get to this part. Will update here once I've made my way through it. + - Can rent it on kindle + - Answers: + - [Solutions](http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition)) + - [Solutions](http://blog.panictank.net/category/algorithmndesignmanualsolutions/page/2/) + - [Errata](http://www3.cs.stonybrook.edu/~skiena/algorist/book/errata) - [Write Great Code: Volume 1: Understanding the Machine](https://www.amazon.com/Write-Great-Code-Understanding-Machine/dp/1593270038) - - The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief. - - The author invented [HLA](https://en.wikipedia.org/wiki/High_Level_Assembly), so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like. - - These chapters are worth the read to give you a nice foundation: - - Chapter 2 - Numeric Representation - - Chapter 3 - Binary Arithmetic and Bit Operations - - Chapter 4 - Floating-Point Representation - - Chapter 5 - Character Representation - - Chapter 6 - Memory Organization and Access - - Chapter 7 - Composite Data Types and Memory Objects - - Chapter 9 - CPU Architecture - - Chapter 10 - Instruction Set Architecture - - Chapter 11 - Memory Architecture and Organization + - The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief. + - The author invented [HLA](https://en.wikipedia.org/wiki/High_Level_Assembly), so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like. + - These chapters are worth the read to give you a nice foundation: + - Chapter 2 - Numeric Representation + - Chapter 3 - Binary Arithmetic and Bit Operations + - Chapter 4 - Floating-Point Representation + - Chapter 5 - Character Representation + - Chapter 6 - Memory Organization and Access + - Chapter 7 - Composite Data Types and Memory Objects + - Chapter 9 - CPU Architecture + - Chapter 10 - Instruction Set Architecture + - Chapter 11 - Memory Architecture and Organization - [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844) - - - **Important:** Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently. - - aka CLR, sometimes CLRS, because Stein was late to the game + - **Important:** Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently. + - aka CLR, sometimes CLRS, because Stein was late to the game - [Computer Architecture, Sixth Edition: A Quantitative Approach](https://www.amazon.com/dp/0128119055) - - - For a richer, more up-to-date (2017), but longer treatment + - For a richer, more up-to-date (2017), but longer treatment - [Programming Pearls](http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880) - - The first couple of chapters present clever solutions to programming problems (some very old using data tape) but - that is just an intro. This a guidebook on program design and architecture. + - The first couple of chapters present clever solutions to programming problems (some very old using data tape) but + that is just an intro. This a guidebook on program design and architecture. ## Additional Learning - - I added them to help you become a well-rounded software engineer, and to be aware of certain + + I added them to help you become a well-rounded software engineer, and to be aware of certain technologies and algorithms, so you'll have a bigger toolbox. - ### Compilers - - - [How a Compiler Works in ~1 minute (video)](https://www.youtube.com/watch?v=IhC7sdYe-Jg) - - [Harvard CS50 - Compilers (video)](https://www.youtube.com/watch?v=CSZLNYF4Klo) - - [C++ (video)](https://www.youtube.com/watch?v=twodd1KFfGk) - - [Understanding Compiler Optimization (C++) (video)](https://www.youtube.com/watch?v=FnGCDLhaxKU) + - [How a Compiler Works in ~1 minute (video)](https://www.youtube.com/watch?v=IhC7sdYe-Jg) + - [Harvard CS50 - Compilers (video)](https://www.youtube.com/watch?v=CSZLNYF4Klo) + - [C++ (video)](https://www.youtube.com/watch?v=twodd1KFfGk) + - [Understanding Compiler Optimization (C++) (video)](https://www.youtube.com/watch?v=FnGCDLhaxKU) - ### Emacs and vi(m) - - - Familiarize yourself with a unix-based code editor - - vi(m): - - [Editing With vim 01 - Installation, Setup, and The Modes (video)](https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr) - - [VIM Adventures](http://vim-adventures.com/) - - set of 4 videos: - - [The vi/vim editor - Lesson 1](https://www.youtube.com/watch?v=SI8TeVMX8pk) - - [The vi/vim editor - Lesson 2](https://www.youtube.com/watch?v=F3OO7ZIOaJE) - - [The vi/vim editor - Lesson 3](https://www.youtube.com/watch?v=ZYEccA_nMaI) - - [The vi/vim editor - Lesson 4](https://www.youtube.com/watch?v=1lYD5gwgZIA) - - [Using Vi Instead of Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Using_Vi_instead_of_Emacs) - - emacs: - - [Basics Emacs Tutorial (video)](https://www.youtube.com/watch?v=hbmV1bnQ-i0) - - set of 3 (videos): - - [Emacs Tutorial (Beginners) -Part 1- File commands, cut/copy/paste, cursor commands](https://www.youtube.com/watch?v=ujODL7MD04Q) - - [Emacs Tutorial (Beginners) -Part 2- Buffer management, search, M-x grep and rgrep modes](https://www.youtube.com/watch?v=XWpsRupJ4II) - - [Emacs Tutorial (Beginners) -Part 3- Expressions, Statements, ~/.emacs file and packages](https://www.youtube.com/watch?v=paSgzPso-yc) - - [Evil Mode: Or, How I Learned to Stop Worrying and Love Emacs (video)](https://www.youtube.com/watch?v=JWD1Fpdd4Pc) - - [Writing C Programs With Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Writing_C_programs_with_Emacs) - - [(maybe) Org Mode In Depth: Managing Structure (video)](https://www.youtube.com/watch?v=nsGYet02bEk) + - Familiarize yourself with a unix-based code editor + - vi(m): + - [Editing With vim 01 - Installation, Setup, and The Modes (video)](https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr) + - [VIM Adventures](http://vim-adventures.com/) + - set of 4 videos: + - [The vi/vim editor - Lesson 1](https://www.youtube.com/watch?v=SI8TeVMX8pk) + - [The vi/vim editor - Lesson 2](https://www.youtube.com/watch?v=F3OO7ZIOaJE) + - [The vi/vim editor - Lesson 3](https://www.youtube.com/watch?v=ZYEccA_nMaI) + - [The vi/vim editor - Lesson 4](https://www.youtube.com/watch?v=1lYD5gwgZIA) + - [Using Vi Instead of Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Using_Vi_instead_of_Emacs) + - emacs: + - [Basics Emacs Tutorial (video)](https://www.youtube.com/watch?v=hbmV1bnQ-i0) + - set of 3 (videos): + - [Emacs Tutorial (Beginners) -Part 1- File commands, cut/copy/paste, cursor commands](https://www.youtube.com/watch?v=ujODL7MD04Q) + - [Emacs Tutorial (Beginners) -Part 2- Buffer management, search, M-x grep and rgrep modes](https://www.youtube.com/watch?v=XWpsRupJ4II) + - [Emacs Tutorial (Beginners) -Part 3- Expressions, Statements, ~/.emacs file and packages](https://www.youtube.com/watch?v=paSgzPso-yc) + - [Evil Mode: Or, How I Learned to Stop Worrying and Love Emacs (video)](https://www.youtube.com/watch?v=JWD1Fpdd4Pc) + - [Writing C Programs With Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Writing_C_programs_with_Emacs) + - [(maybe) Org Mode In Depth: Managing Structure (video)](https://www.youtube.com/watch?v=nsGYet02bEk) - ### Unix command line tools - - - I filled in the list below from good tools. - - bash - - cat - - grep - - sed - - awk - - curl or wget - - sort - - tr - - uniq - - [strace](https://en.wikipedia.org/wiki/Strace) - - [tcpdump](https://danielmiessler.com/study/tcpdump/) + - I filled in the list below from good tools. + - bash + - cat + - grep + - sed + - awk + - curl or wget + - sort + - tr + - uniq + - [strace](https://en.wikipedia.org/wiki/Strace) + - [tcpdump](https://danielmiessler.com/study/tcpdump/) - ### Information theory (videos) - - - [Khan Academy](https://www.khanacademy.org/computing/computer-science/informationtheory) - - more about Markov processes: - - [Core Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation) - - [Core Implementing Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation) - - [Project = Markov Text Generation Walk Through](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/EUjrq/project-markov-text-generation-walk-through) - - See more in MIT 6.050J Information and Entropy series below. + - [Khan Academy](https://www.khanacademy.org/computing/computer-science/informationtheory) + - more about Markov processes: + - [Core Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation) + - [Core Implementing Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation) + - [Project = Markov Text Generation Walk Through](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/EUjrq/project-markov-text-generation-walk-through) + - See more in MIT 6.050J Information and Entropy series below. - ### Parity & Hamming Code (videos) - - - [Intro](https://www.youtube.com/watch?v=q-3BctoUpHE) - - [Parity](https://www.youtube.com/watch?v=DdMcAUlxh1M) - - Hamming Code: - - [Error detection](https://www.youtube.com/watch?v=1A_NcXxdoCc) - - [Error correction](https://www.youtube.com/watch?v=JAMLuxdHH8o) - - [Error Checking](https://www.youtube.com/watch?v=wbH2VxzmoZk) + - [Intro](https://www.youtube.com/watch?v=q-3BctoUpHE) + - [Parity](https://www.youtube.com/watch?v=DdMcAUlxh1M) + - Hamming Code: + - [Error detection](https://www.youtube.com/watch?v=1A_NcXxdoCc) + - [Error correction](https://www.youtube.com/watch?v=JAMLuxdHH8o) + - [Error Checking](https://www.youtube.com/watch?v=wbH2VxzmoZk) - ### Entropy - - - also see videos below - - make sure to watch information theory videos first - - [Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits (video)](https://youtu.be/JnJq3Py0dyM?t=176) + - also see videos below + - make sure to watch information theory videos first + - [Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits (video)](https://youtu.be/JnJq3Py0dyM?t=176) - ### Cryptography - - - also see videos below - - make sure to watch information theory videos first - - [Khan Academy Series](https://www.khanacademy.org/computing/computer-science/cryptography) - - [Cryptography: Hash Functions](https://www.youtube.com/watch?v=KqqOXndnvic&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=30) - - [Cryptography: Encryption](https://www.youtube.com/watch?v=9TNI2wHmaeI&index=31&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) + - also see videos below + - make sure to watch information theory videos first + - [Khan Academy Series](https://www.khanacademy.org/computing/computer-science/cryptography) + - [Cryptography: Hash Functions](https://www.youtube.com/watch?v=KqqOXndnvic&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=30) + - [Cryptography: Encryption](https://www.youtube.com/watch?v=9TNI2wHmaeI&index=31&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - ### Compression - - - make sure to watch information theory videos first - - Computerphile (videos): - - [Compression](https://www.youtube.com/watch?v=Lto-ajuqW3w) - - [Entropy in Compression](https://www.youtube.com/watch?v=M5c_RFKVkko) - - [Upside Down Trees (Huffman Trees)](https://www.youtube.com/watch?v=umTbivyJoiI) - - [EXTRA BITS/TRITS - Huffman Trees](https://www.youtube.com/watch?v=DV8efuB3h2g) - - [Elegant Compression in Text (The LZ 77 Method)](https://www.youtube.com/watch?v=goOa3DGezUA) - - [Text Compression Meets Probabilities](https://www.youtube.com/watch?v=cCDCfoHTsaU) - - [Compressor Head videos](https://www.youtube.com/playlist?list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H) - - [(optional) Google Developers Live: GZIP is not enough!](https://www.youtube.com/watch?v=whGwm0Lky2s) + - make sure to watch information theory videos first + - Computerphile (videos): + - [Compression](https://www.youtube.com/watch?v=Lto-ajuqW3w) + - [Entropy in Compression](https://www.youtube.com/watch?v=M5c_RFKVkko) + - [Upside Down Trees (Huffman Trees)](https://www.youtube.com/watch?v=umTbivyJoiI) + - [EXTRA BITS/TRITS - Huffman Trees](https://www.youtube.com/watch?v=DV8efuB3h2g) + - [Elegant Compression in Text (The LZ 77 Method)](https://www.youtube.com/watch?v=goOa3DGezUA) + - [Text Compression Meets Probabilities](https://www.youtube.com/watch?v=cCDCfoHTsaU) + - [Compressor Head videos](https://www.youtube.com/playlist?list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H) + - [(optional) Google Developers Live: GZIP is not enough!](https://www.youtube.com/watch?v=whGwm0Lky2s) - ### Computer Security - - - [MIT (23 videos)](https://www.youtube.com/playlist?list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - - [Introduction, Threat Models](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - - [Control Hijacking Attacks](https://www.youtube.com/watch?v=6bwzNg5qQ0o&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=2) - - [Buffer Overflow Exploits and Defenses](https://www.youtube.com/watch?v=drQyrzRoRiA&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=3) - - [Privilege Separation](https://www.youtube.com/watch?v=6SIJmoE9L9g&index=4&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - - [Capabilities](https://www.youtube.com/watch?v=8VqTSY-11F4&index=5&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - - [Sandboxing Native Code](https://www.youtube.com/watch?v=VEV74hwASeU&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=6) - - [Web Security Model](https://www.youtube.com/watch?v=chkFBigodIw&index=7&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - - [Securing Web Applications](https://www.youtube.com/watch?v=EBQIGy1ROLY&index=8&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - - [Symbolic Execution](https://www.youtube.com/watch?v=yRVZPvHYHzw&index=9&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - - [Network Security](https://www.youtube.com/watch?v=SIEVvk3NVuk&index=11&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - - [Network Protocols](https://www.youtube.com/watch?v=QOtA76ga_fY&index=12&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - - [Side-Channel Attacks](https://www.youtube.com/watch?v=PuVMkSEcPiI&index=15&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [MIT (23 videos)](https://www.youtube.com/playlist?list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [Introduction, Threat Models](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [Control Hijacking Attacks](https://www.youtube.com/watch?v=6bwzNg5qQ0o&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=2) + - [Buffer Overflow Exploits and Defenses](https://www.youtube.com/watch?v=drQyrzRoRiA&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=3) + - [Privilege Separation](https://www.youtube.com/watch?v=6SIJmoE9L9g&index=4&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [Capabilities](https://www.youtube.com/watch?v=8VqTSY-11F4&index=5&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [Sandboxing Native Code](https://www.youtube.com/watch?v=VEV74hwASeU&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=6) + - [Web Security Model](https://www.youtube.com/watch?v=chkFBigodIw&index=7&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [Securing Web Applications](https://www.youtube.com/watch?v=EBQIGy1ROLY&index=8&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [Symbolic Execution](https://www.youtube.com/watch?v=yRVZPvHYHzw&index=9&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [Network Security](https://www.youtube.com/watch?v=SIEVvk3NVuk&index=11&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [Network Protocols](https://www.youtube.com/watch?v=QOtA76ga_fY&index=12&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) + - [Side-Channel Attacks](https://www.youtube.com/watch?v=PuVMkSEcPiI&index=15&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh) - ### Garbage collection - - - [GC in Python (video)](https://www.youtube.com/watch?v=iHVs_HkjdmI) - - [Deep Dive Java: Garbage Collection is Good!](https://www.infoq.com/presentations/garbage-collection-benefits) - - [Deep Dive Python: Garbage Collection in CPython (video)](https://www.youtube.com/watch?v=P-8Z0-MhdQs&list=PLdzf4Clw0VbOEWOS_sLhT_9zaiQDrS5AR&index=3) + - [GC in Python (video)](https://www.youtube.com/watch?v=iHVs_HkjdmI) + - [Deep Dive Java: Garbage Collection is Good!](https://www.infoq.com/presentations/garbage-collection-benefits) + - [Deep Dive Python: Garbage Collection in CPython (video)](https://www.youtube.com/watch?v=P-8Z0-MhdQs&list=PLdzf4Clw0VbOEWOS_sLhT_9zaiQDrS5AR&index=3) - ### Parallel Programming - - - [Coursera (Scala)](https://www.coursera.org/learn/parprog1/home/week/1) - - [Efficient Python for High Performance Parallel Computing (video)](https://www.youtube.com/watch?v=uY85GkaYzBk) + - [Coursera (Scala)](https://www.coursera.org/learn/parprog1/home/week/1) + - [Efficient Python for High Performance Parallel Computing (video)](https://www.youtube.com/watch?v=uY85GkaYzBk) - ### Messaging, Serialization, and Queueing Systems + - [Thrift](https://thrift.apache.org/) + - [Tutorial](http://thrift-tutorial.readthedocs.io/en/latest/intro.html) + - [Protocol Buffers](https://developers.google.com/protocol-buffers/) + - [Tutorials](https://developers.google.com/protocol-buffers/docs/tutorials) + - [gRPC](http://www.grpc.io/) + - [gRPC 101 for Java Developers (video)](https://www.youtube.com/watch?v=5tmPvSe7xXQ&list=PLcTqM9n_dieN0k1nSeN36Z_ppKnvMJoly&index=1) + - [Redis](http://redis.io/) + - [Tutorial](http://try.redis.io/) + - [Amazon SQS (queue)](https://aws.amazon.com/sqs/) + - [Amazon SNS (pub-sub)](https://aws.amazon.com/sns/) + - [RabbitMQ](https://www.rabbitmq.com/) + - [Get Started](https://www.rabbitmq.com/getstarted.html) + - [Celery](http://www.celeryproject.org/) + - [First Steps With Celery](http://docs.celeryproject.org/en/latest/getting-started/first-steps-with-celery.html) + - [ZeroMQ](http://zeromq.org/) + - [Intro - Read The Manual](http://zeromq.org/intro:read-the-manual) + - [ActiveMQ](http://activemq.apache.org/) + - [Kafka](http://kafka.apache.org/documentation.html#introduction) + - [MessagePack](http://msgpack.org/index.html) + - [Avro](https://avro.apache.org/) - - [Thrift](https://thrift.apache.org/) - - [Tutorial](http://thrift-tutorial.readthedocs.io/en/latest/intro.html) - - [Protocol Buffers](https://developers.google.com/protocol-buffers/) - - [Tutorials](https://developers.google.com/protocol-buffers/docs/tutorials) - - [gRPC](http://www.grpc.io/) - - [gRPC 101 for Java Developers (video)](https://www.youtube.com/watch?v=5tmPvSe7xXQ&list=PLcTqM9n_dieN0k1nSeN36Z_ppKnvMJoly&index=1) - - [Redis](http://redis.io/) - - [Tutorial](http://try.redis.io/) - - [Amazon SQS (queue)](https://aws.amazon.com/sqs/) - - [Amazon SNS (pub-sub)](https://aws.amazon.com/sns/) - - [RabbitMQ](https://www.rabbitmq.com/) - - [Get Started](https://www.rabbitmq.com/getstarted.html) - - [Celery](http://www.celeryproject.org/) - - [First Steps With Celery](http://docs.celeryproject.org/en/latest/getting-started/first-steps-with-celery.html) - - [ZeroMQ](http://zeromq.org/) - - [Intro - Read The Manual](http://zeromq.org/intro:read-the-manual) - - [ActiveMQ](http://activemq.apache.org/) - - [Kafka](http://kafka.apache.org/documentation.html#introduction) - - [MessagePack](http://msgpack.org/index.html) - - [Avro](https://avro.apache.org/) - -- ### A\* - - - [A Search Algorithm](https://en.wikipedia.org/wiki/A*_search_algorithm) - - [A\* Pathfinding Tutorial (video)](https://www.youtube.com/watch?v=KNXfSOx4eEE) - - [A\* Pathfinding (E01: algorithm explanation) (video)](https://www.youtube.com/watch?v=-L-WgKMFuhE) +- ### A* + - [A Search Algorithm](https://en.wikipedia.org/wiki/A*_search_algorithm) + - [A* Pathfinding Tutorial (video)](https://www.youtube.com/watch?v=KNXfSOx4eEE) + - [A* Pathfinding (E01: algorithm explanation) (video)](https://www.youtube.com/watch?v=-L-WgKMFuhE) - ### Fast Fourier Transform - - - [An Interactive Guide To The Fourier Transform](https://betterexplained.com/articles/an-interactive-guide-to-the-fourier-transform/) - - [What is a Fourier transform? What is it used for?](http://www.askamathematician.com/2012/09/q-what-is-a-fourier-transform-what-is-it-used-for/) - - [What is the Fourier Transform? (video)](https://www.youtube.com/watch?v=Xxut2PN-V8Q) - - [Divide & Conquer: FFT (video)](https://www.youtube.com/watch?v=iTMn0Kt18tg&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=4) - - [Understanding The FFT](http://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/) + - [An Interactive Guide To The Fourier Transform](https://betterexplained.com/articles/an-interactive-guide-to-the-fourier-transform/) + - [What is a Fourier transform? What is it used for?](http://www.askamathematician.com/2012/09/q-what-is-a-fourier-transform-what-is-it-used-for/) + - [What is the Fourier Transform? (video)](https://www.youtube.com/watch?v=Xxut2PN-V8Q) + - [Divide & Conquer: FFT (video)](https://www.youtube.com/watch?v=iTMn0Kt18tg&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=4) + - [Understanding The FFT](http://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/) - ### Bloom Filter - - - Given a Bloom filter with m bits and k hashing functions, both insertion and membership testing are O(k) - - [Bloom Filters (video)](https://www.youtube.com/watch?v=-SuTGoFYjZs) - - [Bloom Filters | Mining of Massive Datasets | Stanford University (video)](https://www.youtube.com/watch?v=qBTdukbzc78) - - [Tutorial](http://billmill.org/bloomfilter-tutorial/) - - [How To Write A Bloom Filter App](http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/) + - Given a Bloom filter with m bits and k hashing functions, both insertion and membership testing are O(k) + - [Bloom Filters (video)](https://www.youtube.com/watch?v=-SuTGoFYjZs) + - [Bloom Filters | Mining of Massive Datasets | Stanford University (video)](https://www.youtube.com/watch?v=qBTdukbzc78) + - [Tutorial](http://billmill.org/bloomfilter-tutorial/) + - [How To Write A Bloom Filter App](http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/) - ### HyperLogLog - - - [How To Count A Billion Distinct Objects Using Only 1.5KB Of Memory](http://highscalability.com/blog/2012/4/5/big-data-counting-how-to-count-a-billion-distinct-objects-us.html) + - [How To Count A Billion Distinct Objects Using Only 1.5KB Of Memory](http://highscalability.com/blog/2012/4/5/big-data-counting-how-to-count-a-billion-distinct-objects-us.html) - ### Locality-Sensitive Hashing - - - used to determine the similarity of documents - - the opposite of MD5 or SHA which are used to determine if 2 documents/strings are exactly the same. - - [Simhashing (hopefully) made simple](http://ferd.ca/simhashing-hopefully-made-simple.html) + - used to determine the similarity of documents + - the opposite of MD5 or SHA which are used to determine if 2 documents/strings are exactly the same. + - [Simhashing (hopefully) made simple](http://ferd.ca/simhashing-hopefully-made-simple.html) - ### van Emde Boas Trees - - - [Divide & Conquer: van Emde Boas Trees (video)](https://www.youtube.com/watch?v=hmReJCupbNU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=6) - - [MIT Lecture Notes](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2012/lecture-notes/MIT6_046JS12_lec15.pdf) + - [Divide & Conquer: van Emde Boas Trees (video)](https://www.youtube.com/watch?v=hmReJCupbNU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=6) + - [MIT Lecture Notes](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2012/lecture-notes/MIT6_046JS12_lec15.pdf) - ### Augmented Data Structures - - - [CS 61B Lecture 39: Augmenting Data Structures](https://archive.org/details/ucberkeley_webcast_zksIj9O8_jc) + - [CS 61B Lecture 39: Augmenting Data Structures](https://archive.org/details/ucberkeley_webcast_zksIj9O8_jc) - ### Balanced search trees + - Know at least one type of balanced binary tree (and know how it's implemented): + - "Among balanced search trees, AVL and 2/3 trees are now passé, and red-black trees seem to be more popular. + A particularly interesting self-organizing data structure is the splay tree, which uses rotations + to move any accessed key to the root." - Skiena + - Of these, I chose to implement a splay tree. From what I've read, you won't implement a + balanced search tree in your interview. But I wanted exposure to coding one up + and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code. + - splay tree: insert, search, delete functions + If you end up implementing red/black tree try just these: + - search and insertion functions, skipping delete + - I want to learn more about B-Tree since it's used so widely with very large data sets. + - [Self-balancing binary search tree](https://en.wikipedia.org/wiki/Self-balancing_binary_search_tree) - - Know at least one type of balanced binary tree (and know how it's implemented): - - "Among balanced search trees, AVL and 2/3 trees are now passé, and red-black trees seem to be more popular. - A particularly interesting self-organizing data structure is the splay tree, which uses rotations - to move any accessed key to the root." - Skiena - - Of these, I chose to implement a splay tree. From what I've read, you won't implement a - balanced search tree in your interview. But I wanted exposure to coding one up - and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code. - - splay tree: insert, search, delete functions - If you end up implementing red/black tree try just these: - - search and insertion functions, skipping delete - - I want to learn more about B-Tree since it's used so widely with very large data sets. - - [Self-balancing binary search tree](https://en.wikipedia.org/wiki/Self-balancing_binary_search_tree) + - **AVL trees** + - In practice: + From what I can tell, these aren't used much in practice, but I could see where they would be: + The AVL tree is another structure supporting O(log n) search, insertion, and removal. It is more rigidly + balanced than red–black trees, leading to slower insertion and removal but faster retrieval. This makes it + attractive for data structures that may be built once and loaded without reconstruction, such as language + dictionaries (or program dictionaries, such as the opcodes of an assembler or interpreter). + - [MIT AVL Trees / AVL Sort (video)](https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6) + - [AVL Trees (video)](https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees) + - [AVL Tree Implementation (video)](https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation) + - [Split And Merge](https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge) - - **AVL trees** + - **Splay trees** + - In practice: + Splay trees are typically used in the implementation of caches, memory allocators, routers, garbage collectors, + data compression, ropes (replacement of string used for long text strings), in Windows NT (in the virtual memory, + networking and file system code) etc. + - [CS 61B: Splay Trees (video)](https://archive.org/details/ucberkeley_webcast_G5QIXywcJlY) + - MIT Lecture: Splay Trees: + - Gets very mathy, but watch the last 10 minutes for sure. + - [Video](https://www.youtube.com/watch?v=QnPl_Y6EqMo) - - In practice: - From what I can tell, these aren't used much in practice, but I could see where they would be: - The AVL tree is another structure supporting O(log n) search, insertion, and removal. It is more rigidly - balanced than red–black trees, leading to slower insertion and removal but faster retrieval. This makes it - attractive for data structures that may be built once and loaded without reconstruction, such as language - dictionaries (or program dictionaries, such as the opcodes of an assembler or interpreter). - - [MIT AVL Trees / AVL Sort (video)](https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6) - - [AVL Trees (video)](https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees) - - [AVL Tree Implementation (video)](https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation) - - [Split And Merge](https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge) + - **Red/black trees** + - these are a translation of a 2-3 tree (see below) + - In practice: + Red–black trees offer worst-case guarantees for insertion time, deletion time, and search time. + Not only does this make them valuable in time-sensitive applications such as real-time applications, + but it makes them valuable building blocks in other data structures which provide worst-case guarantees; + for example, many data structures used in computational geometry can be based on red–black trees, and + the Completely Fair Scheduler used in current Linux kernels uses red–black trees. In the version 8 of Java, + the Collection HashMap has been modified such that instead of using a LinkedList to store identical elements with poor + hashcodes, a Red-Black tree is used. + - [Aduni - Algorithms - Lecture 4 (link jumps to starting point) (video)](https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871) + - [Aduni - Algorithms - Lecture 5 (video)](https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5) + - [Red-Black Tree](https://en.wikipedia.org/wiki/Red%E2%80%93black_tree) + - [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/competitive-programming/tutorials/an-introduction-to-binary-search-and-red-black-trees/) - - **Splay trees** + - **2-3 search trees** + - In practice: + 2-3 trees have faster inserts at the expense of slower searches (since height is more compared to AVL trees). + - You would use 2-3 tree very rarely because its implementation involves different types of nodes. Instead, people use Red Black trees. + - [23-Tree Intuition and Definition (video)](https://www.youtube.com/watch?v=C3SsdUqasD4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=2) + - [Binary View of 23-Tree](https://www.youtube.com/watch?v=iYvBtGKsqSg&index=3&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) + - [2-3 Trees (student recitation) (video)](https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - - In practice: - Splay trees are typically used in the implementation of caches, memory allocators, routers, garbage collectors, - data compression, ropes (replacement of string used for long text strings), in Windows NT (in the virtual memory, - networking and file system code) etc. - - [CS 61B: Splay Trees (video)](https://archive.org/details/ucberkeley_webcast_G5QIXywcJlY) - - MIT Lecture: Splay Trees: - - Gets very mathy, but watch the last 10 minutes for sure. - - [Video](https://www.youtube.com/watch?v=QnPl_Y6EqMo) + - **2-3-4 Trees (aka 2-4 trees)** + - In practice: + For every 2-4 tree, there are corresponding red–black trees with data elements in the same order. The insertion and deletion + operations on 2-4 trees are also equivalent to color-flipping and rotations in red–black trees. This makes 2-4 trees an + important tool for understanding the logic behind red–black trees, and this is why many introductory algorithm texts introduce + 2-4 trees just before red–black trees, even though **2-4 trees are not often used in practice**. + - [CS 61B Lecture 26: Balanced Search Trees (video)](https://archive.org/details/ucberkeley_webcast_zqrqYXkth6Q) + - [Bottom Up 234-Trees (video)](https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) + - [Top Down 234-Trees (video)](https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5) - - **Red/black trees** + - **N-ary (K-ary, M-ary) trees** + - note: the N or K is the branching factor (max branches) + - binary trees are a 2-ary tree, with branching factor = 2 + - 2-3 trees are 3-ary + - [K-Ary Tree](https://en.wikipedia.org/wiki/K-ary_tree) - - these are a translation of a 2-3 tree (see below) - - In practice: - Red–black trees offer worst-case guarantees for insertion time, deletion time, and search time. - Not only does this make them valuable in time-sensitive applications such as real-time applications, - but it makes them valuable building blocks in other data structures which provide worst-case guarantees; - for example, many data structures used in computational geometry can be based on red–black trees, and - the Completely Fair Scheduler used in current Linux kernels uses red–black trees. In the version 8 of Java, - the Collection HashMap has been modified such that instead of using a LinkedList to store identical elements with poor - hashcodes, a Red-Black tree is used. - - [Aduni - Algorithms - Lecture 4 (link jumps to starting point) (video)](https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871) - - [Aduni - Algorithms - Lecture 5 (video)](https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5) - - [Red-Black Tree](https://en.wikipedia.org/wiki/Red%E2%80%93black_tree) - - [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/competitive-programming/tutorials/an-introduction-to-binary-search-and-red-black-trees/) + - **B-Trees** + - fun fact: it's a mystery, but the B could stand for Boeing, Balanced, or Bayer (co-inventor) + - In Practice: + B-Trees are widely used in databases. Most modern filesystems use B-trees (or Variants). In addition to + its use in databases, the B-tree is also used in filesystems to allow quick random access to an arbitrary + block in a particular file. The basic problem is turning the file block i address into a disk block + (or perhaps to a cylinder-head-sector) address. + - [B-Tree](https://en.wikipedia.org/wiki/B-tree) + - [B-Tree Datastructure](http://btechsmartclass.com/data_structures/b-trees.html) + - [Introduction to B-Trees (video)](https://www.youtube.com/watch?v=I22wEC1tTGo&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=6) + - [B-Tree Definition and Insertion (video)](https://www.youtube.com/watch?v=s3bCdZGrgpA&index=7&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) + - [B-Tree Deletion (video)](https://www.youtube.com/watch?v=svfnVhJOfMc&index=8&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) + - [MIT 6.851 - Memory Hierarchy Models (video)](https://www.youtube.com/watch?v=V3omVLzI0WE&index=7&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf) + - covers cache-oblivious B-Trees, very interesting data structures + - the first 37 minutes are very technical, may be skipped (B is block size, cache line size) - - **2-3 search trees** - - In practice: - 2-3 trees have faster inserts at the expense of slower searches (since height is more compared to AVL trees). - - You would use 2-3 tree very rarely because its implementation involves different types of nodes. Instead, people use Red Black trees. - - [23-Tree Intuition and Definition (video)](https://www.youtube.com/watch?v=C3SsdUqasD4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=2) - - [Binary View of 23-Tree](https://www.youtube.com/watch?v=iYvBtGKsqSg&index=3&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) - - [2-3 Trees (student recitation) (video)](https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) +- ### k-D Trees + - great for finding number of points in a rectangle or higher dimension object + - a good fit for k-nearest neighbors + - [Kd Trees (video)](https://www.youtube.com/watch?v=W94M9D_yXKk) + - [kNN K-d tree algorithm (video)](https://www.youtube.com/watch?v=Y4ZgLlDfKDg) - - **2-3-4 Trees (aka 2-4 trees)** +- ### Skip lists + - "These are somewhat of a cult data structure" - Skiena + - [Randomization: Skip Lists (video)](https://www.youtube.com/watch?v=2g9OSRKJuzM&index=10&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) + - [For animations and a little more detail](https://en.wikipedia.org/wiki/Skip_list) - - In practice: - For every 2-4 tree, there are corresponding red–black trees with data elements in the same order. The insertion and deletion - operations on 2-4 trees are also equivalent to color-flipping and rotations in red–black trees. This makes 2-4 trees an - important tool for understanding the logic behind red–black trees, and this is why many introductory algorithm texts introduce - 2-4 trees just before red–black trees, even though **2-4 trees are not often used in practice**. - - [CS 61B Lecture 26: Balanced Search Trees (video)](https://archive.org/details/ucberkeley_webcast_zqrqYXkth6Q) - - [Bottom Up 234-Trees (video)](https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) - - [Top Down 234-Trees (video)](https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5) +- ### Network Flows + - [Ford-Fulkerson in 5 minutes — Step by step example (video)](https://www.youtube.com/watch?v=Tl90tNtKvxs) + - [Ford-Fulkerson Algorithm (video)](https://www.youtube.com/watch?v=v1VgJmkEJW0) + - [Network Flows (video)](https://www.youtube.com/watch?v=2vhN4Ice5jI) - - **N-ary (K-ary, M-ary) trees** +- ### Disjoint Sets & Union Find + - [UCB 61B - Disjoint Sets; Sorting & selection (video)](https://archive.org/details/ucberkeley_webcast_MAEGXTwmUsI) + - [Sedgewick Algorithms - Union-Find (6 videos)](https://www.coursera.org/learn/algorithms-part1/home/week/1) - - note: the N or K is the branching factor (max branches) - - binary trees are a 2-ary tree, with branching factor = 2 - - 2-3 trees are 3-ary - - [K-Ary Tree](https://en.wikipedia.org/wiki/K-ary_tree) +- ### Math for Fast Processing + - [Integer Arithmetic, Karatsuba Multiplication (video)](https://www.youtube.com/watch?v=eCaXlAaN2uE&index=11&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) + - [The Chinese Remainder Theorem (used in cryptography) (video)](https://www.youtube.com/watch?v=ru7mWZJlRQg) - - **B-Trees** - - fun fact: it's a mystery, but the B could stand for Boeing, Balanced, or Bayer (co-inventor) - - In Practice: - B-Trees are widely used in databases. Most modern filesystems use B-trees (or Variants). In addition to - its use in databases, the B-tree is also used in filesystems to allow quick random access to an arbitrary - block in a particular file. The basic problem is turning the file block i address into a disk block - (or perhaps to a cylinder-head-sector) address. - - [B-Tree](https://en.wikipedia.org/wiki/B-tree) - - [B-Tree Datastructure](http://btechsmartclass.com/data_structures/b-trees.html) - - [Introduction to B-Trees (video)](https://www.youtube.com/watch?v=I22wEC1tTGo&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=6) - - [B-Tree Definition and Insertion (video)](https://www.youtube.com/watch?v=s3bCdZGrgpA&index=7&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) - - [B-Tree Deletion (video)](https://www.youtube.com/watch?v=svfnVhJOfMc&index=8&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) - - [MIT 6.851 - Memory Hierarchy Models (video)](https://www.youtube.com/watch?v=V3omVLzI0WE&index=7&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf) - covers cache-oblivious B-Trees, very interesting data structures - the first 37 minutes are very technical, may be skipped (B is block size, cache line size) +- ### Treap + - Combination of a binary search tree and a heap + - [Treap](https://en.wikipedia.org/wiki/Treap) + - [Data Structures: Treaps explained (video)](https://www.youtube.com/watch?v=6podLUYinH8) + - [Applications in set operations](https://www.cs.cmu.edu/~scandal/papers/treaps-spaa98.pdf) -* ### k-D Trees +- ### Linear Programming (videos) + - [Linear Programming](https://www.youtube.com/watch?v=M4K6HYLHREQ) + - [Finding minimum cost](https://www.youtube.com/watch?v=2ACJ9ewUC6U) + - [Finding maximum value](https://www.youtube.com/watch?v=8AA_81xI3ik) + - [Solve Linear Equations with Python - Simplex Algorithm](https://www.youtube.com/watch?v=44pAWI7v5Zk) - - great for finding number of points in a rectangle or higher dimension object - - a good fit for k-nearest neighbors - - [Kd Trees (video)](https://www.youtube.com/watch?v=W94M9D_yXKk) - - [kNN K-d tree algorithm (video)](https://www.youtube.com/watch?v=Y4ZgLlDfKDg) +- ### Geometry, Convex hull (videos) + - [Graph Alg. IV: Intro to geometric algorithms - Lecture 9](https://youtu.be/XIAQRlNkJAw?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3164) + - [Geometric Algorithms: Graham & Jarvis - Lecture 10](https://www.youtube.com/watch?v=J5aJEcOr6Eo&index=10&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) + - [Divide & Conquer: Convex Hull, Median Finding](https://www.youtube.com/watch?v=EzeYI7p9MjU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=2) -* ### Skip lists +- ### Discrete math + - see videos below - - "These are somewhat of a cult data structure" - Skiena - - [Randomization: Skip Lists (video)](https://www.youtube.com/watch?v=2g9OSRKJuzM&index=10&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - - [For animations and a little more detail](https://en.wikipedia.org/wiki/Skip_list) - -* ### Network Flows - - - [Ford-Fulkerson in 5 minutes — Step by step example (video)](https://www.youtube.com/watch?v=Tl90tNtKvxs) - - [Ford-Fulkerson Algorithm (video)](https://www.youtube.com/watch?v=v1VgJmkEJW0) - - [Network Flows (video)](https://www.youtube.com/watch?v=2vhN4Ice5jI) - -* ### Disjoint Sets & Union Find - - - [UCB 61B - Disjoint Sets; Sorting & selection (video)](https://archive.org/details/ucberkeley_webcast_MAEGXTwmUsI) - - [Sedgewick Algorithms - Union-Find (6 videos)](https://www.coursera.org/learn/algorithms-part1/home/week/1) - -* ### Math for Fast Processing - - - [Integer Arithmetic, Karatsuba Multiplication (video)](https://www.youtube.com/watch?v=eCaXlAaN2uE&index=11&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [The Chinese Remainder Theorem (used in cryptography) (video)](https://www.youtube.com/watch?v=ru7mWZJlRQg) - -* ### Treap - - - Combination of a binary search tree and a heap - - [Treap](https://en.wikipedia.org/wiki/Treap) - - [Data Structures: Treaps explained (video)](https://www.youtube.com/watch?v=6podLUYinH8) - - [Applications in set operations](https://www.cs.cmu.edu/~scandal/papers/treaps-spaa98.pdf) - -* ### Linear Programming (videos) - - - [Linear Programming](https://www.youtube.com/watch?v=M4K6HYLHREQ) - - [Finding minimum cost](https://www.youtube.com/watch?v=2ACJ9ewUC6U) - - [Finding maximum value](https://www.youtube.com/watch?v=8AA_81xI3ik) - - [Solve Linear Equations with Python - Simplex Algorithm](https://www.youtube.com/watch?v=44pAWI7v5Zk) - -* ### Geometry, Convex hull (videos) - - - [Graph Alg. IV: Intro to geometric algorithms - Lecture 9](https://youtu.be/XIAQRlNkJAw?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3164) - - [Geometric Algorithms: Graham & Jarvis - Lecture 10](https://www.youtube.com/watch?v=J5aJEcOr6Eo&index=10&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) - - [Divide & Conquer: Convex Hull, Median Finding](https://www.youtube.com/watch?v=EzeYI7p9MjU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=2) - -* ### Discrete math - - - see videos below - -* ### Machine Learning - - Why ML? - - [How Google Is Remaking Itself As A Machine Learning First Company](https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70) - - [Large-Scale Deep Learning for Intelligent Computer Systems (video)](https://www.youtube.com/watch?v=QSaZGT4-6EY) - - [Deep Learning and Understandability versus Software Engineering and Verification by Peter Norvig](https://www.youtube.com/watch?v=X769cyzBNVw) - - [Google's Cloud Machine learning tools (video)](https://www.youtube.com/watch?v=Ja2hxBAwG_0) - - [Google Developers' Machine Learning Recipes (Scikit Learn & Tensorflow) (video)](https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal) - - [Tensorflow (video)](https://www.youtube.com/watch?v=oZikw5k_2FM) - - [Tensorflow Tutorials](https://www.tensorflow.org/versions/r0.11/tutorials/index.html) - - [Practical Guide to implementing Neural Networks in Python (using Theano)](http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/) - - Courses: - - [Great starter course: Machine Learning](https://www.coursera.org/learn/machine-learning) - [videos only](https://www.youtube.com/playlist?list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW) - see videos 12-18 for a review of linear algebra (14 and 15 are duplicates) - - [Neural Networks for Machine Learning](https://www.coursera.org/learn/neural-networks) - - [Google's Deep Learning Nanodegree](https://www.udacity.com/course/deep-learning--ud730) - - [Google/Kaggle Machine Learning Engineer Nanodegree](https://www.udacity.com/course/machine-learning-engineer-nanodegree-by-google--nd009) - - [Self-Driving Car Engineer Nanodegree](https://www.udacity.com/drive) - - [Metis Online Course (\$99 for 2 months)](http://www.thisismetis.com/explore-data-science) - - Resources: - - Books: - - [Python Machine Learning](https://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/) - - [Data Science from Scratch: First Principles with Python](https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X) - - [Introduction to Machine Learning with Python](https://www.amazon.com/Introduction-Machine-Learning-Python-Scientists/dp/1449369413/) - - [Machine Learning for Software Engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers) - - Data School: http://www.dataschool.io/ +- ### Machine Learning + - Why ML? + - [How Google Is Remaking Itself As A Machine Learning First Company](https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70) + - [Large-Scale Deep Learning for Intelligent Computer Systems (video)](https://www.youtube.com/watch?v=QSaZGT4-6EY) + - [Deep Learning and Understandability versus Software Engineering and Verification by Peter Norvig](https://www.youtube.com/watch?v=X769cyzBNVw) + - [Google's Cloud Machine learning tools (video)](https://www.youtube.com/watch?v=Ja2hxBAwG_0) + - [Google Developers' Machine Learning Recipes (Scikit Learn & Tensorflow) (video)](https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal) + - [Tensorflow (video)](https://www.youtube.com/watch?v=oZikw5k_2FM) + - [Tensorflow Tutorials](https://www.tensorflow.org/versions/r0.11/tutorials/index.html) + - [Practical Guide to implementing Neural Networks in Python (using Theano)](http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/) + - Courses: + - [Great starter course: Machine Learning](https://www.coursera.org/learn/machine-learning) + - [videos only](https://www.youtube.com/playlist?list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW) + - see videos 12-18 for a review of linear algebra (14 and 15 are duplicates) + - [Neural Networks for Machine Learning](https://www.coursera.org/learn/neural-networks) + - [Google's Deep Learning Nanodegree](https://www.udacity.com/course/deep-learning--ud730) + - [Google/Kaggle Machine Learning Engineer Nanodegree](https://www.udacity.com/course/machine-learning-engineer-nanodegree-by-google--nd009) + - [Self-Driving Car Engineer Nanodegree](https://www.udacity.com/drive) + - [Metis Online Course ($99 for 2 months)](http://www.thisismetis.com/explore-data-science) + - Resources: + - Books: + - [Python Machine Learning](https://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/) + - [Data Science from Scratch: First Principles with Python](https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X) + - [Introduction to Machine Learning with Python](https://www.amazon.com/Introduction-Machine-Learning-Python-Scientists/dp/1449369413/) + - [Machine Learning for Software Engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers) + - Data School: http://www.dataschool.io/ --- @@ -1848,89 +1782,85 @@ You're never really done. above because it's just too much. It's easy to overdo it on a subject. You want to get hired in this century, right? -- **SOLID** - - [ ] [Bob Martin SOLID Principles of Object Oriented and Agile Design (video)](https://www.youtube.com/watch?v=TMuno5RZNeE) - - [ ] S - [Single Responsibility Principle](http://www.oodesign.com/single-responsibility-principle.html) | [Single responsibility to each Object](http://www.javacodegeeks.com/2011/11/solid-single-responsibility-principle.html) - - [more flavor](https://docs.google.com/open?id=0ByOwmqah_nuGNHEtcU5OekdDMkk) - - [ ] O - [Open/Closed Principal](http://www.oodesign.com/open-close-principle.html) | [On production level Objects are ready for extension but not for modification](https://en.wikipedia.org/wiki/Open/closed_principle) - - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgN2M5MTkwM2EtNWFkZC00ZTI3LWFjZTUtNTFhZGZiYmUzODc1&hl=en) - - [ ] L - [Liskov Substitution Principal](http://www.oodesign.com/liskov-s-substitution-principle.html) | [Base Class and Derived class follow ‘IS A’ principal](http://stackoverflow.com/questions/56860/what-is-the-liskov-substitution-principle) - - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgNzAzZjA5ZmItNjU3NS00MzQ5LTkwYjMtMDJhNDU5ZTM0MTlh&hl=en) - - [ ] I - [Interface segregation principle](http://www.oodesign.com/interface-segregation-principle.html) | clients should not be forced to implement interfaces they don't use - - [Interface Segregation Principle in 5 minutes (video)](https://www.youtube.com/watch?v=3CtAfl7aXAQ) - - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgOTViYjJhYzMtMzYxMC00MzFjLWJjMzYtOGJiMDc5N2JkYmJi&hl=en) - - [ ] D -[Dependency Inversion principle](http://www.oodesign.com/dependency-inversion-principle.html) | Reduce the dependency In composition of objects. - - [Why Is The Dependency Inversion Principle And Why Is It Important](http://stackoverflow.com/questions/62539/what-is-the-dependency-inversion-principle-and-why-is-it-important) - - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgMjdlMWIzNGUtZTQ0NC00ZjQ5LTkwYzQtZjRhMDRlNTQ3ZGMz&hl=en) +- **SOLID** + - [ ] [Bob Martin SOLID Principles of Object Oriented and Agile Design (video)](https://www.youtube.com/watch?v=TMuno5RZNeE) + - [ ] S - [Single Responsibility Principle](http://www.oodesign.com/single-responsibility-principle.html) | [Single responsibility to each Object](http://www.javacodegeeks.com/2011/11/solid-single-responsibility-principle.html) + - [more flavor](https://docs.google.com/open?id=0ByOwmqah_nuGNHEtcU5OekdDMkk) + - [ ] O - [Open/Closed Principal](http://www.oodesign.com/open-close-principle.html) | [On production level Objects are ready for extension but not for modification](https://en.wikipedia.org/wiki/Open/closed_principle) + - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgN2M5MTkwM2EtNWFkZC00ZTI3LWFjZTUtNTFhZGZiYmUzODc1&hl=en) + - [ ] L - [Liskov Substitution Principal](http://www.oodesign.com/liskov-s-substitution-principle.html) | [Base Class and Derived class follow ‘IS A’ principal](http://stackoverflow.com/questions/56860/what-is-the-liskov-substitution-principle) + - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgNzAzZjA5ZmItNjU3NS00MzQ5LTkwYjMtMDJhNDU5ZTM0MTlh&hl=en) + - [ ] I - [Interface segregation principle](http://www.oodesign.com/interface-segregation-principle.html) | clients should not be forced to implement interfaces they don't use + - [Interface Segregation Principle in 5 minutes (video)](https://www.youtube.com/watch?v=3CtAfl7aXAQ) + - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgOTViYjJhYzMtMzYxMC00MzFjLWJjMzYtOGJiMDc5N2JkYmJi&hl=en) + - [ ] D -[Dependency Inversion principle](http://www.oodesign.com/dependency-inversion-principle.html) | Reduce the dependency In composition of objects. + - [Why Is The Dependency Inversion Principle And Why Is It Important](http://stackoverflow.com/questions/62539/what-is-the-dependency-inversion-principle-and-why-is-it-important) + - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgMjdlMWIzNGUtZTQ0NC00ZjQ5LTkwYzQtZjRhMDRlNTQ3ZGMz&hl=en) -* **Union-Find** - - [Overview](https://www.coursera.org/learn/data-structures/lecture/JssSY/overview) - - [Naive Implementation](https://www.coursera.org/learn/data-structures/lecture/EM5D0/naive-implementations) - - [Trees](https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees) - - [Union By Rank](https://www.coursera.org/learn/data-structures/lecture/qb4c2/union-by-rank) - - [Path Compression](https://www.coursera.org/learn/data-structures/lecture/Q9CVI/path-compression) - - [Analysis Options](https://www.coursera.org/learn/data-structures/lecture/GQQLN/analysis-optional) +- **Union-Find** + - [Overview](https://www.coursera.org/learn/data-structures/lecture/JssSY/overview) + - [Naive Implementation](https://www.coursera.org/learn/data-structures/lecture/EM5D0/naive-implementations) + - [Trees](https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees) + - [Union By Rank](https://www.coursera.org/learn/data-structures/lecture/qb4c2/union-by-rank) + - [Path Compression](https://www.coursera.org/learn/data-structures/lecture/Q9CVI/path-compression) + - [Analysis Options](https://www.coursera.org/learn/data-structures/lecture/GQQLN/analysis-optional) -* **More Dynamic Programming** (videos) +- **More Dynamic Programming** (videos) + - [6.006: Dynamic Programming I: Fibonacci, Shortest Paths](https://www.youtube.com/watch?v=OQ5jsbhAv_M&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=19) + - [6.006: Dynamic Programming II: Text Justification, Blackjack](https://www.youtube.com/watch?v=ENyox7kNKeY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=20) + - [6.006: DP III: Parenthesization, Edit Distance, Knapsack](https://www.youtube.com/watch?v=ocZMDMZwhCY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=21) + - [6.006: DP IV: Guitar Fingering, Tetris, Super Mario Bros.](https://www.youtube.com/watch?v=tp4_UXaVyx8&index=22&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) + - [6.046: Dynamic Programming & Advanced DP](https://www.youtube.com/watch?v=Tw1k46ywN6E&index=14&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) + - [6.046: Dynamic Programming: All-Pairs Shortest Paths](https://www.youtube.com/watch?v=NzgFUwOaoIw&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=15) + - [6.046: Dynamic Programming (student recitation)](https://www.youtube.com/watch?v=krZI60lKPek&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=12) - - [6.006: Dynamic Programming I: Fibonacci, Shortest Paths](https://www.youtube.com/watch?v=OQ5jsbhAv_M&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=19) - - [6.006: Dynamic Programming II: Text Justification, Blackjack](https://www.youtube.com/watch?v=ENyox7kNKeY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=20) - - [6.006: DP III: Parenthesization, Edit Distance, Knapsack](https://www.youtube.com/watch?v=ocZMDMZwhCY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=21) - - [6.006: DP IV: Guitar Fingering, Tetris, Super Mario Bros.](https://www.youtube.com/watch?v=tp4_UXaVyx8&index=22&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [6.046: Dynamic Programming & Advanced DP](https://www.youtube.com/watch?v=Tw1k46ywN6E&index=14&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - - [6.046: Dynamic Programming: All-Pairs Shortest Paths](https://www.youtube.com/watch?v=NzgFUwOaoIw&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=15) - - [6.046: Dynamic Programming (student recitation)](https://www.youtube.com/watch?v=krZI60lKPek&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=12) +- **Advanced Graph Processing** (videos) + - [Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=mUBmcbbJNf4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=27) + - [Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=kQ-UQAzcnzA&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=28) -* **Advanced Graph Processing** (videos) +- MIT **Probability** (mathy, and go slowly, which is good for mathy things) (videos): + - [MIT 6.042J - Probability Introduction](https://www.youtube.com/watch?v=SmFwFdESMHI&index=18&list=PLB7540DEDD482705B) + - [MIT 6.042J - Conditional Probability](https://www.youtube.com/watch?v=E6FbvM-FGZ8&index=19&list=PLB7540DEDD482705B) + - [MIT 6.042J - Independence](https://www.youtube.com/watch?v=l1BCv3qqW4A&index=20&list=PLB7540DEDD482705B) + - [MIT 6.042J - Random Variables](https://www.youtube.com/watch?v=MOfhhFaQdjw&list=PLB7540DEDD482705B&index=21) + - [MIT 6.042J - Expectation I](https://www.youtube.com/watch?v=gGlMSe7uEkA&index=22&list=PLB7540DEDD482705B) + - [MIT 6.042J - Expectation II](https://www.youtube.com/watch?v=oI9fMUqgfxY&index=23&list=PLB7540DEDD482705B) + - [MIT 6.042J - Large Deviations](https://www.youtube.com/watch?v=q4mwO2qS2z4&index=24&list=PLB7540DEDD482705B) + - [MIT 6.042J - Random Walks](https://www.youtube.com/watch?v=56iFMY8QW2k&list=PLB7540DEDD482705B&index=25) - - [Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=mUBmcbbJNf4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=27) - - [Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=kQ-UQAzcnzA&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=28) +- [Simonson: Approximation Algorithms (video)](https://www.youtube.com/watch?v=oDniZCmNmNw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=19) -* MIT **Probability** (mathy, and go slowly, which is good for mathy things) (videos): +- **String Matching** + - Rabin-Karp (videos): + - [Rabin Karps Algorithm](https://www.coursera.org/learn/data-structures/lecture/c0Qkw/rabin-karps-algorithm) + - [Precomputing](https://www.coursera.org/learn/data-structures/lecture/nYrc8/optimization-precomputation) + - [Optimization: Implementation and Analysis](https://www.coursera.org/learn/data-structures/lecture/h4ZLc/optimization-implementation-and-analysis) + - [Table Doubling, Karp-Rabin](https://www.youtube.com/watch?v=BRO7mVIFt08&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=9) + - [Rolling Hashes, Amortized Analysis](https://www.youtube.com/watch?v=w6nuXg0BISo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=32) + - Knuth-Morris-Pratt (KMP): + - [TThe Knuth-Morris-Pratt (KMP) String Matching Algorithm](https://www.youtube.com/watch?v=5i7oKodCRJo) + - Boyer–Moore string search algorithm + - [Boyer-Moore String Search Algorithm](https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm) + - [Advanced String Searching Boyer-Moore-Horspool Algorithms (video)](https://www.youtube.com/watch?v=QDZpzctPf10) + - [Coursera: Algorithms on Strings](https://www.coursera.org/learn/algorithms-on-strings/home/week/1) + - starts off great, but by the time it gets past KMP it gets more complicated than it needs to be + - nice explanation of tries + - can be skipped - - [MIT 6.042J - Probability Introduction](https://www.youtube.com/watch?v=SmFwFdESMHI&index=18&list=PLB7540DEDD482705B) - - [MIT 6.042J - Conditional Probability](https://www.youtube.com/watch?v=E6FbvM-FGZ8&index=19&list=PLB7540DEDD482705B) - - [MIT 6.042J - Independence](https://www.youtube.com/watch?v=l1BCv3qqW4A&index=20&list=PLB7540DEDD482705B) - - [MIT 6.042J - Random Variables](https://www.youtube.com/watch?v=MOfhhFaQdjw&list=PLB7540DEDD482705B&index=21) - - [MIT 6.042J - Expectation I](https://www.youtube.com/watch?v=gGlMSe7uEkA&index=22&list=PLB7540DEDD482705B) - - [MIT 6.042J - Expectation II](https://www.youtube.com/watch?v=oI9fMUqgfxY&index=23&list=PLB7540DEDD482705B) - - [MIT 6.042J - Large Deviations](https://www.youtube.com/watch?v=q4mwO2qS2z4&index=24&list=PLB7540DEDD482705B) - - [MIT 6.042J - Random Walks](https://www.youtube.com/watch?v=56iFMY8QW2k&list=PLB7540DEDD482705B&index=25) +- **Sorting** -* [Simonson: Approximation Algorithms (video)](https://www.youtube.com/watch?v=oDniZCmNmNw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=19) - -* **String Matching** - - - Rabin-Karp (videos): - - [Rabin Karps Algorithm](https://www.coursera.org/learn/data-structures/lecture/c0Qkw/rabin-karps-algorithm) - - [Precomputing](https://www.coursera.org/learn/data-structures/lecture/nYrc8/optimization-precomputation) - - [Optimization: Implementation and Analysis](https://www.coursera.org/learn/data-structures/lecture/h4ZLc/optimization-implementation-and-analysis) - - [Table Doubling, Karp-Rabin](https://www.youtube.com/watch?v=BRO7mVIFt08&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=9) - - [Rolling Hashes, Amortized Analysis](https://www.youtube.com/watch?v=w6nuXg0BISo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=32) - - Knuth-Morris-Pratt (KMP): - - [TThe Knuth-Morris-Pratt (KMP) String Matching Algorithm](https://www.youtube.com/watch?v=5i7oKodCRJo) - - Boyer–Moore string search algorithm - - [Boyer-Moore String Search Algorithm](https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm) - - [Advanced String Searching Boyer-Moore-Horspool Algorithms (video)](https://www.youtube.com/watch?v=QDZpzctPf10) - - [Coursera: Algorithms on Strings](https://www.coursera.org/learn/algorithms-on-strings/home/week/1) - - starts off great, but by the time it gets past KMP it gets more complicated than it needs to be - - nice explanation of tries - - can be skipped - -* **Sorting** - - - Stanford lectures on sorting: - - [Lecture 15 | Programming Abstractions (video)](https://www.youtube.com/watch?v=ENp00xylP7c&index=15&list=PLFE6E58F856038C69) - - [Lecture 16 | Programming Abstractions (video)](https://www.youtube.com/watch?v=y4M9IVgrVKo&index=16&list=PLFE6E58F856038C69) - - Shai Simonson, [Aduni.org](http://www.aduni.org/): - - [Algorithms - Sorting - Lecture 2 (video)](https://www.youtube.com/watch?v=odNJmw5TOEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=2) - - [Algorithms - Sorting II - Lecture 3 (video)](https://www.youtube.com/watch?v=hj8YKFTFKEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=3) - - Steven Skiena lectures on sorting: - - [lecture begins at 26:46 (video)](https://youtu.be/ute-pmMkyuk?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1600) - - [lecture begins at 27:40 (video)](https://www.youtube.com/watch?v=yLvp-pB8mak&index=8&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [lecture begins at 35:00 (video)](https://www.youtube.com/watch?v=q7K9otnzlfE&index=9&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [lecture begins at 23:50 (video)](https://www.youtube.com/watch?v=TvqIGu9Iupw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=10) + - Stanford lectures on sorting: + - [Lecture 15 | Programming Abstractions (video)](https://www.youtube.com/watch?v=ENp00xylP7c&index=15&list=PLFE6E58F856038C69) + - [Lecture 16 | Programming Abstractions (video)](https://www.youtube.com/watch?v=y4M9IVgrVKo&index=16&list=PLFE6E58F856038C69) + - Shai Simonson, [Aduni.org](http://www.aduni.org/): + - [Algorithms - Sorting - Lecture 2 (video)](https://www.youtube.com/watch?v=odNJmw5TOEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=2) + - [Algorithms - Sorting II - Lecture 3 (video)](https://www.youtube.com/watch?v=hj8YKFTFKEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=3) + - Steven Skiena lectures on sorting: + - [lecture begins at 26:46 (video)](https://youtu.be/ute-pmMkyuk?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1600) + - [lecture begins at 27:40 (video)](https://www.youtube.com/watch?v=yLvp-pB8mak&index=8&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [lecture begins at 35:00 (video)](https://www.youtube.com/watch?v=q7K9otnzlfE&index=9&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [lecture begins at 23:50 (video)](https://www.youtube.com/watch?v=TvqIGu9Iupw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=10) ## Video Series @@ -1951,8 +1881,7 @@ Sit back and enjoy. "Netflix and skill" :P - [Discrete Mathematics Part 1 by Sarada Herke (5 videos)](https://www.youtube.com/playlist?list=PLGxuz-nmYlQPOc4w1Kp2MZrdqOOm4Jxeo) - CSE373 - Analysis of Algorithms (25 videos) - - - [Skiena lectures from Algorithm Design Manual](https://www.youtube.com/watch?v=ZFjhkohHdAA&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=1) + - [Skiena lectures from Algorithm Design Manual](https://www.youtube.com/watch?v=ZFjhkohHdAA&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=1) - [UC Berkeley 61B (Spring 2014): Data Structures (25 videos)](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd) @@ -1991,8 +1920,7 @@ Sit back and enjoy. "Netflix and skill" :P - [Stanford: Programming Paradigms (27 videos)](https://www.youtube.com/view_play_list?p=9D558D49CA734A02) - [Introduction to Cryptography by Christof Paar](https://www.youtube.com/playlist?list=PL6N5qY2nvvJE8X75VkXglSrVhLv1tVcfy) - - - [Course Website along with Slides and Problem Sets](http://www.crypto-textbook.com/) + - [Course Website along with Slides and Problem Sets](http://www.crypto-textbook.com/) - [Mining Massive Datasets - Stanford University (94 videos)](https://www.youtube.com/playlist?list=PLLssT5z_DsK9JDLcT8T62VtzwyW9LNepV) @@ -2007,34 +1935,35 @@ Sit back and enjoy. "Netflix and skill" :P - [Love classic papers?](https://www.cs.cmu.edu/~crary/819-f09/) - [1978: Communicating Sequential Processes](http://spinroot.com/courses/summer/Papers/hoare_1978.pdf) - - [implemented in Go](https://godoc.org/github.com/thomas11/csp) + - [implemented in Go](https://godoc.org/github.com/thomas11/csp) - [2003: The Google File System](http://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf) - - replaced by Colossus in 2012 -- [2004: MapReduce: Simplified Data Processing on Large Clusters](http://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf) - - mostly replaced by Cloud Dataflow? + - replaced by Colossus in 2012 +- [2004: MapReduce: Simplified Data Processing on Large Clusters]( http://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf) + - mostly replaced by Cloud Dataflow? - [2006: Bigtable: A Distributed Storage System for Structured Data](https://static.googleusercontent.com/media/research.google.com/en//archive/bigtable-osdi06.pdf) - - [An Inside Look at Google BigQuery](https://cloud.google.com/files/BigQueryTechnicalWP.pdf) + - [An Inside Look at Google BigQuery](https://cloud.google.com/files/BigQueryTechnicalWP.pdf) - [2006: The Chubby Lock Service for Loosely-Coupled Distributed Systems](https://research.google.com/archive/chubby-osdi06.pdf) - [2007: Dynamo: Amazon’s Highly Available Key-value Store](http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.pdf) - - The Dynamo paper kicked off the NoSQL revolution + - The Dynamo paper kicked off the NoSQL revolution - [2007: What Every Programmer Should Know About Memory (very long, and the author encourages skipping of some sections)](https://www.akkadia.org/drepper/cpumemory.pdf) - [2010: Dapper, a Large-Scale Distributed Systems Tracing Infrastructure](https://research.google.com/pubs/archive/36356.pdf) - [2010: Dremel: Interactive Analysis of Web-Scale Datasets](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36632.pdf) - [2012: Google's Colossus](https://www.wired.com/2012/07/google-colossus/) - - paper not available + - paper not available - 2012: AddressSanitizer: A Fast Address Sanity Checker: - - [paper](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf) - - [video](https://www.usenix.org/conference/atc12/technical-sessions/presentation/serebryany) + - [paper](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf) + - [video](https://www.usenix.org/conference/atc12/technical-sessions/presentation/serebryany) - 2013: Spanner: Google’s Globally-Distributed Database: - - [paper](http://static.googleusercontent.com/media/research.google.com/en//archive/spanner-osdi2012.pdf) - - [video](https://www.usenix.org/node/170855) + - [paper](http://static.googleusercontent.com/media/research.google.com/en//archive/spanner-osdi2012.pdf) + - [video](https://www.usenix.org/node/170855) - [2014: Machine Learning: The High-Interest Credit Card of Technical Debt](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43146.pdf) - [2015: Continuous Pipelines at Google](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf) - [2015: High-Availability at Massive Scale: Building Google’s Data Infrastructure for Ads](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44686.pdf) -- [2015: TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](http://download.tensorflow.org/paper/whitepaper2015.pdf) +- [2015: TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](http://download.tensorflow.org/paper/whitepaper2015.pdf ) - [2015: How Developers Search for Code: A Case Study](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf) - [2016: Borg, Omega, and Kubernetes](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf) + ## LICENSE [CC-BY-SA-4.0](./LICENSE.txt)