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@ -351,7 +351,7 @@ You could also use these, but read around first. There may be caveats:
Here is an article I wrote about choosing a language for the interview:
[Pick One Language for the Coding Interview](https://startupnextdoor.com/important-pick-one-language-for-the-coding-interview/).
This is the original article my post was based on: http://blog.codingforinterviews.com/best-programming-language-jobs/
This is the original article my post was based on: [Choosing a Programming Language for Interviews](https://web.archive.org/web/20210516054124/http://blog.codingforinterviews.com/best-programming-language-jobs/)
You need to be very comfortable in the language and be knowledgeable.
@ -806,7 +806,7 @@ if you can identify the runtime complexity of different algorithms. It's a super
- ### Heap / Priority Queue / Binary Heap
- 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)
- [ ] [Introduction (video)](https://www.coursera.org/lecture/data-structures/introduction-2OpTs)
- [ ] [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)
@ -814,8 +814,8 @@ if you can identify the runtime complexity of different algorithms. It's a super
- [ ] [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)
- [ ] [Heap Sort (video)](https://www.coursera.org/lecture/data-structures/heap-sort-hSzMO)
- [ ] [Building a heap (video)](https://www.coursera.org/lecture/data-structures/building-a-heap-dwrOS)
- [ ] [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)
@ -848,17 +848,17 @@ if you can identify the runtime complexity of different algorithms. It's a super
- 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)
- [ ] [1. Mergesort](https://www.coursera.org/lecture/algorithms-part1/mergesort-ARWDq)
- [ ] [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)
- [ ] [3. Sorting Complexity](https://www.coursera.org/lecture/algorithms-part1/sorting-complexity-xAltF)
- [ ] [4. Comparators](https://www.coursera.org/lecture/algorithms-part1/comparators-9FYhS)
- [ ] [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)
- [ ] [2. Selection](https://www.coursera.org/lecture/algorithms-part1/selection-UQxFT)
- [ ] [3. Duplicate Keys](https://www.coursera.org/lecture/algorithms-part1/duplicate-keys-XvjPd)
- [ ] [4. System Sorts](https://www.coursera.org/lecture/algorithms-part1/system-sorts-QBNZ7)
- [ ] UC Berkeley:
- [ ] [CS 61B Lecture 29: Sorting I (video)](https://archive.org/details/ucberkeley_webcast_EiUvYS2DT6I)
@ -892,10 +892,10 @@ if you can identify the runtime complexity of different algorithms. It's a super
- [ ] 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)
- [ ] [2. Key Indexed Counting](https://www.coursera.org/lecture/algorithms-part2/key-indexed-counting-2pi1Z)
- [ ] [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)
- [ ] [5. 3 Way Radix Quicksort](https://www.coursera.org/lecture/algorithms-part2/3-way-radix-quicksort-crkd5)
- [ ] [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)
@ -1000,11 +1000,11 @@ Graphs can be used to represent many problems in computer science, so this secti
- [ ] [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)
- [ ] [A dynamic programming algorithm (video)](https://www.coursera.org/lecture/algorithmic-thinking-2/a-dynamic-programming-algorithm-PSonq)
- [ ] [Illustrating the DP algorithm (video)](https://www.coursera.org/lecture/algorithmic-thinking-2/illustrating-the-dp-algorithm-oUEK2)
- [ ] [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)
- [ ] [Global pairwise sequence alignment (video)](https://www.coursera.org/lecture/algorithmic-thinking-2/global-pairwise-sequence-alignment-UZ7o6)
- [ ] [Local pairwise sequence alignment (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/WnNau/local-pairwise-sequence-alignment)
- ### Design patterns
@ -1100,8 +1100,8 @@ Graphs can be used to represent many problems in computer science, so this secti
- 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)
- [Paging, segmentation and virtual memory (video)](https://youtu.be/O4nwUqQodAg)
- [Interrupts (video)](https://youtu.be/iKlAWIKEyuw)
- 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.
@ -1136,11 +1136,11 @@ Graphs can be used to represent many problems in computer science, so this secti
- ### 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)
- [ ] [1. Introduction to Substring Search](https://www.coursera.org/lecture/algorithms-part2/introduction-to-substring-search-n3ZpG)
- [ ] [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)
- [ ] [5. Rabin-Karp](https://www.coursera.org/lecture/algorithms-part2/rabin-karp-3KiqT)
- [ ] [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).
@ -1165,7 +1165,6 @@ Graphs can be used to represent many problems in computer science, so this secti
- ### 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)
@ -1346,8 +1345,7 @@ You're never really done.
- This book is better as an algorithm reference, and not something you read cover to cover.
- 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/)
- [Solutions](https://web.archive.org/web/20150404194210/http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition))
- [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
@ -1394,7 +1392,7 @@ You're never really done.
- [ ] [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/)
- [ ] [Database Normalization - 1NF, 2NF, 3NF and 4NF (video)](https://www.youtube.com/watch?v=UrYLYV7WSHM)
- [ ] [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - There are a lot of resources in this one. Look through the articles and examples. I put some of them below
- [ ] [How to ace a systems design interview](http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/)
- [ ] [How to ace a systems design interview](https://web.archive.org/web/20120716060051/http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/)
- [ ] [Numbers Everyone Should Know](http://everythingisdata.wordpress.com/2009/10/17/numbers-everyone-should-know/)
- [ ] [How long does it take to make a context switch?](http://blog.tsunanet.net/2010/11/how-long-does-it-take-to-make-context.html)
- [ ] [Transactions Across Datacenters (video)](https://www.youtube.com/watch?v=srOgpXECblk)
@ -1478,7 +1476,7 @@ You're never really done.
- [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/)
- [Design a cache system](https://web.archive.org/web/20220217064329/https://adayinthelifeof.nl/2011/02/06/memcache-internals/)
## Additional Learning
@ -1615,7 +1613,6 @@ You're never really done.
- ### 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
@ -1792,15 +1789,14 @@ You're never really done.
- [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)
- [Tensorflow Tutorials](https://www.tensorflow.org/tutorials)
- [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)
- [AWS Machine Learning Engineer Nanodegree](https://www.udacity.com/course/aws-machine-learning-engineer-nanodegree--nd189)
- [Self-Driving Car Engineer Nanodegree](https://www.udacity.com/drive)
- Resources:
- Books:
@ -1869,7 +1865,7 @@ You're never really done.
- **String Matching**
- Rabin-Karp (videos):
- [Rabin Karps Algorithm](https://www.coursera.org/learn/data-structures/lecture/c0Qkw/rabin-karps-algorithm)
- [Rabin Karps Algorithm](https://www.coursera.org/lecture/data-structures/rabin-karps-algorithm-c0Qkw)
- [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)

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@ -48,7 +48,6 @@
- [Data Structures And Algorithms in Python](https://www.youtube.com/watch?v=kQDxmjfkIKY)
- Java
- [Stanford CS106A - Programming Methodology (video)](https://see.stanford.edu/Course/CS106A)
- [Software Construction In Java (video)](https://www.edx.org/course/software-construction-java-mitx-6-005-1x)
- [Introduction To Programming In Java](http://introcs.cs.princeton.edu/java/home/)
- [Algorithms 4th Ed - Algorithm Book In Java](http://algs4.cs.princeton.edu/home/)
- [Effective Java 3rd Edition](https://www.amazon.com/Effective-Java-Joshua-Bloch-ebook/dp/B078H61SCH)