Python: Real World Machine Learning

Summary

This is the final chapter of the book. We have seen how to do data science at scale on a cluster of machines. Spark is able to train and test machine learning algorithms using all the nodes in a cluster with a simple interface, very similar to Scikit-learn. It's proved that this solution is able to cope with petabytes of information, creating a valid alternative to observation subsampling and online learning.

To become an expert in Spark and streaming processing, we strongly advise you to read the book, Mastering Apache Spark, Mike Frampton, Packt Publishing.

If you're brave enough to switch to Scala, the main programming language for Spark, this book is the best for such a transition: Scala for Data Science, Pascal Bugnion, Packt Publishing ...