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.

View the slides

Additional resources:

About the speaker

Sean Owen
Sean Owen
Director of Data Science at Cloudera & Apache Spark committer

About the conference

dotScale 2016
The European Tech Conference on Scalability
Next edition: dotScale 2017 in Paris, France. Tickets available now!

Liked this talk? Share it!


comments powered by Disqus