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Add a new section for Machine Learning at Scale

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@ -24,6 +24,7 @@ An updated and curated list of selected readings to illustrate High Scalability,
- [Availability](#availability)
- [Stability](#stability)
- [Performance](#performance)
- [ML at Scale](#Machine-Learning)
- [Architectures](#architectures)
- [Ad-hoc](#ad-hoc)
- [Interview](#interview)
@ -332,23 +333,6 @@ An updated and curated list of selected readings to illustrate High Scalability,
* [Store-Forward](https://docs.oracle.com/cd/E13222_01/wls/docs91/saf_admin/overview.html)
* [Request-Reply](https://docs.tibco.com/pub/ftl/4.3.0/doc/html/GUID-A64ABED1-682E-4E1D-A94A-5590CB91B9BB.html)
* [Enterprise Service Bus](http://www.oracle.com/technetwork/articles/soa/ind-soa-esb-1967705.html)
* [Distributed Machine Learning](https://arxiv.org/pdf/1512.09295.pdf)
* [Scalable Deep Learning Platform On Spark In Baidu](https://www.slideshare.net/JenAman/scalable-deep-learning-platform-on-spark-in-baidu)
* [Horovod: Uber’s Open Source Distributed Deep Learning Framework for TensorFlow](https://eng.uber.com/horovod/)
* [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)
* [AIOps in Practice at Baidu](https://www.usenix.org/conference/srecon17asia/program/presentation/qu)
* [Learning with Privacy at Scale - Differential Privacy Team, 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)
* [PaddlePaddle Fluid: Elastic Deep Learning on Kubernetes at Baidu](http://research.baidu.com/paddlepaddle-fluid-elastic-deep-learning-kubernetes/)
* [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)
* [Distributed Source Code and Configuration Files Management](https://betterexplained.com/articles/intro-to-distributed-version-control-illustrated/)
* [Distributed Version Control Systems: A Not-So-Quick Guide Through](https://www.infoq.com/articles/dvcs-guide)
* [Stemma: Distributed Git Server at Palantir](https://medium.com/@palantir/stemma-distributed-git-server-70afbca0fc29)
@ -414,6 +398,24 @@ An updated and curated list of selected readings to illustrate High Scalability,
* [Decreasing RAM Usage by 40% Using jemalloc with Python & Celery at Zapier](https://zapier.com/engineering/celery-python-jemalloc/)
* [Using Java Large Heap (110 GB) for Boosting Site Perpormance at Expedia](https://techblog.expedia.com/2015/09/25/solving-problems-with-very-large-java-heaps/)
## Machine-Learning
* [Scalable Deep Learning Platform On Spark In Baidu](https://www.slideshare.net/JenAman/scalable-deep-learning-platform-on-spark-in-baidu)
* [Horovod: Uber’s Open Source Distributed Deep Learning Framework for TensorFlow](https://eng.uber.com/horovod/)
* [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)
* [AIOps in Practice at Baidu](https://www.usenix.org/conference/srecon17asia/program/presentation/qu)
* [Learning with Privacy at Scale - Differential Privacy Team, 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)
* [PaddlePaddle Fluid: Elastic Deep Learning on Kubernetes at Baidu](http://research.baidu.com/paddlepaddle-fluid-elastic-deep-learning-kubernetes/)
* [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)
## Architectures
* [Architecture of Tripod (Flickr’s Backend)](https://yahooeng.tumblr.com/post/157200523046/introducing-tripod-flickrs-backend-refactored)
* [Architecture of SurveyMonkey](https://engineering.surveymonkey.com/2016/04/09/the-architecture-behind-surveymonkey/)