Scaling Learning on Apache Spark - Sean Owen at dotScale 2016

Scaling up machine learning techniques to keep pace with "big data" is its own interesting engineering problem. Recently, Apache Spark has become a popular framework for large-scale ML. Sean introduces the intuition behind modern large-scale recommenders and highlights four ways ML algorithms are engineered to scale.

Slides

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More details

Additional resources:

Spark documentation: http://spark.apache.org/docs/latest/mllib-collaborative-filtering.html#collaborative-filtering
(Old) introductory blog post discussing Spark and ALS: http://blog.cloudera.com/blog/2014/03/why-apache-spark-is-a-crossover-hit-for-data-scientists/
Plug for "Advanced Analytics with Spark", which covers Spark and ALS in Chapter 3: http://shop.oreilly.com/product/0636920035091.do
Relevant example code to accompany that chapter 3: https://github.com/sryza/aas/tree/master/ch03-recommender