Book Image

Mastering Java for Data Science

By : Alexey Grigorev
Book Image

Mastering Java for Data Science

By: Alexey Grigorev

Overview of this book

Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings.
Table of Contents (17 chapters)
Title Page
About the Author
About the Reviewers
Customer Feedback

Apache Hadoop

Apache Hadoop is a set of tools that allows you to scale your data processing pipelines to thousands of machines. It includes:

  • Hadoop MapReduce: This is a data processing framework
  • HDFS: This is a distributed filesystem, which allows us to store data on multiple machines
  • YARN: This is the executor of MapReduce and other jobs

We will only cover MapReduce, as it is the core of Hadoop and it is related to data processing. We will not cover the rest, and we will also not talk about setting up or configuring a Hadoop Cluster as this is slightly beyond scope for this book. If you are interested in knowing more about it, Hadoop: The Definitive Guide by Tom White is an excellent book for learning this subject in depth. 

In our experiments, we will use the local mode, that is, we will emulate the cluster, but still run the code on a local machine. This is very useful for testing, and once we are sure that it works correctly, it can be deployed to a cluster with no changes. 

Hadoop MapReduce...