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Split the Intelligence section into Big Data and ML

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@ -440,30 +440,38 @@ An updated and curated list of selected readings to illustrate High Scalability,
* [The Process of Optimizing for Client Performance at Expedia](https://techblog.expedia.com/2018/03/09/go-fast-or-go-home-the-process-of-optimizing-for-client-performance/)
## Intelligence
* [AIOps in Practice at Baidu](https://www.usenix.org/conference/srecon17asia/program/presentation/qu)
* [Scalable Deep Learning Platform on Spark at Baidu](https://www.slideshare.net/JenAman/scalable-deep-learning-platform-on-spark-in-baidu)
* [PaddlePaddle Fluid: Elastic Deep Learning on Kubernetes at Baidu](http://research.baidu.com/paddlepaddle-fluid-elastic-deep-learning-kubernetes/)
* [Horovod: Open Source Distributed Deep Learning Framework for TensorFlow at Uber](https://eng.uber.com/horovod/)
* [COTA: Improving Customer Care with NLP & Machine Learning at Uber](https://eng.uber.com/cota/)
* [Repo-Topix: Topic Extraction Framework at Github](https://githubengineering.com/topics/)
* [Scaling Gradient Boosted Trees for Click-Through-Rate Prediction at Yelp](https://engineeringblog.yelp.com/2018/01/building-a-distributed-ml-pipeline-part1.html)
* [TensorFlowOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo](https://yahooeng.tumblr.com/post/157196488076/open-sourcing-tensorflowonspark-distributed-deep)
* [CaffeOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo](https://yahooeng.tumblr.com/post/139916828451/caffeonspark-open-sourced-for-distributed-deep)
* [Learning with Privacy at Scale at Apple](https://machinelearning.apple.com/2017/12/06/learning-with-privacy-at-scale.html)
* [Image Classification Experiment Using Deep Learning at Mercari](https://medium.com/mercari-engineering/mercaris-image-classification-experiment-using-deep-learning-9b4e994a18ec)
* [Content-based Video Relevance Prediction at Hulu](https://medium.com/hulu-tech-blog/content-based-video-relevance-prediction-b2c448e14752)
* [Training ML Models with Airflow and BigQuery at WePay](https://wecode.wepay.com/posts/training-machine-learning-models-with-airflow-and-bigquery)
* [Improving Photo Selection With Deep Learning at TripAdvisor](http://engineering.tripadvisor.com/improving-tripadvisor-photo-selection-deep-learning/)
* [Machine Learning (2 parts) at Condé Nast](https://technology.condenast.com/story/handbag-brand-and-color-detection)
* [Machine Learning Applications In The E-commerce Domain (4 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/07/12/machine-learning-applications-in-the-e-commerce-domain-4/)
* [Venue Rating System at Foursquare](https://engineering.foursquare.com/finding-the-perfect-10-how-we-developed-the-foursquare-venue-rating-system-c76b08f7b9b3)
* [Using Machine Learning to Improve Streaming Quality at Netflix](https://medium.com/netflix-techblog/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f)
* [Box Graph: Spontaneous Social Network at Box](https://blog.box.com/blog/box-graph-how-we-built-spontaneous-social-network/)
* [Improving Video Thumbnails with Deep Neural Nets at YouTube](https://youtube-eng.googleblog.com/2015/10/improving-youtube-video-thumbnails-with_8.html)
* [Quantile Regression for Delivering On Time at Instacart](https://tech.instacart.com/how-instacart-delivers-on-time-using-quantile-regression-2383e2e03edb)
* [Cross-Lingual End-to-End Product Search with Deep Learning at Zalando](https://jobs.zalando.com/tech/blog/search-deep-neural-network/)
* [PricingNet: Pricing Modelling with Neural Networks at Skyscanner](https://hackernoon.com/pricingnet-modelling-the-global-airline-industry-with-neural-networks-833844d20ea6)
* [Machine Learning at Jane Street](https://blog.janestreet.com/real-world-machine-learning-part-1/)
* [Big Data](https://insights.sei.cmu.edu/sei_blog/2017/05/reference-architectures-for-big-data-systems.html)
* [Data Platform at Netflix](https://www.youtube.com/watch?v=CSDIThSwA7s)
* [Data Platform at Flipkart](https://tech.flipkart.com/overview-of-flipkart-data-platform-20c6d3e9a196)
* [Data Infrastructure at GO-JEK](https://blog.gojekengineering.com/data-infrastructure-at-go-jek-cd4dc8cbd929)
* [RBEA: Real-time Analytics Platform at King](https://techblog.king.com/rbea-scalable-real-time-analytics-king/)
* [Gimel: Analytics Data Processing Platform at PayPal](https://www.paypal-engineering.com/2018/04/17/gimel/)
* [AthenaX: Streaming Analytics Platform at Uber](https://eng.uber.com/athenax/)
* [Distributed Machine Learning](https://www.csie.ntu.edu.tw/~cjlin/talks/bigdata-bilbao.pdf)
* [AIOps in Practice at Baidu](https://www.usenix.org/conference/srecon17asia/program/presentation/qu)
* [Scalable Deep Learning Platform on Spark at Baidu](https://www.slideshare.net/JenAman/scalable-deep-learning-platform-on-spark-in-baidu)
* [PaddlePaddle Fluid: Elastic Deep Learning on Kubernetes at Baidu](http://research.baidu.com/paddlepaddle-fluid-elastic-deep-learning-kubernetes/)
* [Horovod: Open Source Distributed Deep Learning Framework for TensorFlow at Uber](https://eng.uber.com/horovod/)
* [COTA: Improving Customer Care with NLP & Machine Learning at Uber](https://eng.uber.com/cota/)
* [Repo-Topix: Topic Extraction Framework at Github](https://githubengineering.com/topics/)
* [Scaling Gradient Boosted Trees for Click-Through-Rate Prediction at Yelp](https://engineeringblog.yelp.com/2018/01/building-a-distributed-ml-pipeline-part1.html)
* [TensorFlowOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo](https://yahooeng.tumblr.com/post/157196488076/open-sourcing-tensorflowonspark-distributed-deep)
* [CaffeOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo](https://yahooeng.tumblr.com/post/139916828451/caffeonspark-open-sourced-for-distributed-deep)
* [Learning with Privacy at Scale at Apple](https://machinelearning.apple.com/2017/12/06/learning-with-privacy-at-scale.html)
* [Image Classification Experiment Using Deep Learning at Mercari](https://medium.com/mercari-engineering/mercaris-image-classification-experiment-using-deep-learning-9b4e994a18ec)
* [Content-based Video Relevance Prediction at Hulu](https://medium.com/hulu-tech-blog/content-based-video-relevance-prediction-b2c448e14752)
* [Training ML Models with Airflow and BigQuery at WePay](https://wecode.wepay.com/posts/training-machine-learning-models-with-airflow-and-bigquery)
* [Improving Photo Selection With Deep Learning at TripAdvisor](http://engineering.tripadvisor.com/improving-tripadvisor-photo-selection-deep-learning/)
* [Machine Learning (2 parts) at Condé Nast](https://technology.condenast.com/story/handbag-brand-and-color-detection)
* [Machine Learning Applications In The E-commerce Domain (4 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/07/12/machine-learning-applications-in-the-e-commerce-domain-4/)
* [Venue Rating System at Foursquare](https://engineering.foursquare.com/finding-the-perfect-10-how-we-developed-the-foursquare-venue-rating-system-c76b08f7b9b3)
* [Using Machine Learning to Improve Streaming Quality at Netflix](https://medium.com/netflix-techblog/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f)
* [Box Graph: Spontaneous Social Network at Box](https://blog.box.com/blog/box-graph-how-we-built-spontaneous-social-network/)
* [Improving Video Thumbnails with Deep Neural Nets at YouTube](https://youtube-eng.googleblog.com/2015/10/improving-youtube-video-thumbnails-with_8.html)
* [Quantile Regression for Delivering On Time at Instacart](https://tech.instacart.com/how-instacart-delivers-on-time-using-quantile-regression-2383e2e03edb)
* [Cross-Lingual End-to-End Product Search with Deep Learning at Zalando](https://jobs.zalando.com/tech/blog/search-deep-neural-network/)
* [PricingNet: Pricing Modelling with Neural Networks at Skyscanner](https://hackernoon.com/pricingnet-modelling-the-global-airline-industry-with-neural-networks-833844d20ea6)
* [Machine Learning at Jane Street](https://blog.janestreet.com/real-world-machine-learning-part-1/)
## Architectures
* [API Platform at Riot Games](https://engineering.riotgames.com/news/riot-games-api-deep-dive)
@ -471,17 +479,14 @@ An updated and curated list of selected readings to illustrate High Scalability,
* [Back-end at Flickr](https://yahooeng.tumblr.com/post/157200523046/introducing-tripod-flickrs-backend-refactored)
* [Back-end at BlaBlaCar](http://blablatech.com/blog/BlaBlaTech-behind-the-scene)
* [Architecture of the Ranking Answers End-to-End at Quora](https://engineering.quora.com/A-Machine-Learning-Approach-to-Ranking-Answers-on-Quora)
* [Data Platform at Flipkart](https://tech.flipkart.com/overview-of-flipkart-data-platform-20c6d3e9a196)
* [Data Infrastructure at GO-JEK](https://blog.gojekengineering.com/data-infrastructure-at-go-jek-cd4dc8cbd929)
* [Stack Overflow Enterprise at Palantir](https://medium.com/@palantir/terraforming-stack-overflow-enterprise-in-aws-47ee431e6be7)
* [Distributed Cron at Quora](https://engineering.quora.com/Quoras-Distributed-Cron-Architecture)
* [Real-Time Presence Platform at LinkedIn](https://engineering.linkedin.com/blog/2018/01/now-you-see-me--now-you-dont--linkedins-real-time-presence-platf)
* [Real-time Analytics Platform at King](https://techblog.king.com/rbea-scalable-real-time-analytics-king/)
* [Simone: Distributed Simulation Service at Netflix](https://medium.com/netflix-techblog/https-medium-com-netflix-techblog-simone-a-distributed-simulation-service-b2c85131ca1b)
* [Seagull: Distributed System that Helps Running > 20 Million Tests Per Day at Yelp](https://engineeringblog.yelp.com/2017/04/how-yelp-runs-millions-of-tests-every-day.html)
* [Cloud Bouncer: Distributed Rate Limiting at Yahoo](https://yahooeng.tumblr.com/post/111288877956/cloud-bouncer-distributed-rate-limiting-at-yahoo)
* [MySQL Realtime Traffic Emulator at KakaoTalk](http://tech.kakao.com/2016/02/16/opensource-2-mtre/)
* [Architecture of Finance and Banking Systems](https://www.sesameindia.com/images/core-banking-system-architecture)
* [Architectures of Finance and Banking Systems](https://www.sesameindia.com/images/core-banking-system-architecture)
* [Reference Architecture For The Open Banking Standard](https://hortonworks.com/blog/reference-architecture-open-banking-standard/)
* [Building a Modern Bank Backend at Monzo](https://monzo.com/blog/2016/09/19/building-a-modern-bank-backend/)
* [Choosing an Architecture for Core Banking System at TrustBK](https://blog.trustbk.com/choosing-an-architecture-85750e1e5a03)