Mastering Machine Learning with Spark 2.x

The purpose of machine learning is to build systems that learn from data. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment.