Machine Learning with Spark · 2nd Edition

Key Features Get to the grips with the latest version of Apache Spark UtilizeSpark's machine learning library to implement predictive analytics LeverageSpark’s powerful tools to load, analyze, clean, and transform your data BookDescription

This book will teach you about popular machine learning algorithms and theirimplementation. You will learn how various machine learning concepts areimplemented in the context of Spark ML. You will start by installing Spark ina single and multinode cluster. Next you'll see how to execute Scala andPython based programs for Spark ML. Then we will take a few datasets and godeeper into clustering, classification, and regression. Toward the end, wewill also cover text processing using Spark ML.

Once you have learned the concepts, they can be applied to implementalgorithms in either green-field implementations or to migrate existingsystems to this new platform. You can migrate from Mahout or Scikit to useSpark ML.

By the end of this book, you will acquire the skills to leverage Spark'sfeatures to create your own scalable machine learning applications and power amodern data-driven business.

What you will learn Get hands-on with the latest version of Spark ML Createyour first Spark program with Scala and Python Set up and configure adevelopment environment for Spark on your own computer, as well as on AmazonEC2 Access public machine learning datasets and use Spark to load, process,clean, and transform data Use Spark's machine learning library to implementprograms by utilizing well-known machine learning models Deal with large-scaletext data, including feature extraction and using text data as input to yourmachine learning models Write Spark functions to evaluate the performance ofyour machine learning models