Book Image

Machine Learning with Spark. - Second Edition

By : Rajdeep Dua, Manpreet Singh Ghotra
Book Image

Machine Learning with Spark. - Second Edition

By: Rajdeep Dua, Manpreet Singh Ghotra

Overview of this book

This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business.
Table of Contents (13 chapters)

Summary

In this chapter, we explored two new unsupervised learning methods, PCA and SVD, for dimensionality reduction. We saw how to extract features for, and train, these models using facial image data. We visualized the results of the model in the form of Eigenfaces, saw how to apply the models to transform our original data into a reduced dimensionality representation, and investigated the close link between PCA and SVD.

In the next chapter, we will delve more deeply into techniques for text processing and analysis with Spark.