Book Image

Large Scale Machine Learning with Python

By : Bastiaan Sjardin, Alberto Boschetti
Book Image

Large Scale Machine Learning with Python

By: Bastiaan Sjardin, Alberto Boschetti

Overview of this book

Large Python machine learning projects involve new problems associated with specialized machine learning architectures and designs that many data scientists have yet to tackle. But finding algorithms and designing and building platforms that deal with large sets of data is a growing need. Data scientists have to manage and maintain increasingly complex data projects, and with the rise of big data comes an increasing demand for computational and algorithmic efficiency. Large Scale Machine Learning with Python uncovers a new wave of machine learning algorithms that meet scalability demands together with a high predictive accuracy. Dive into scalable machine learning and the three forms of scalability. Speed up algorithms that can be used on a desktop computer with tips on parallelization and memory allocation. Get to grips with new algorithms that are specifically designed for large projects and can handle bigger files, and learn about machine learning in big data environments. We will also cover the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python.
Table of Contents (17 chapters)
Large Scale Machine Learning with Python
About the Authors
About the Reviewer

Chapter 8. Distributed Environments – Hadoop and Spark

In this chapter, we will introduce a new way to process data, scaling horizontally. So far, we've focused our attention primarily on processing big data on a standalone machine; here, we will introduce some methods that run on a cluster of machines.

Specifically, we will first illustrate the motivations and circumstances when we need a cluster to process big data. Then, we will introduce the Hadoop framework and all its components with a few examples (HDFS, MapReduce, and YARN), and finally, we will introduce the Spark framework and its Python interface—pySpark.