Filmed at http://2016.dotscale.io on April 25th in Paris. More talks on http://thedotpost.com 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.