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
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Standard Java library


The standard Java library is very rich and offers a lot of tools for data manipulation, including:

  • Collections for organizing data in memory
  • I/O for reading and writing data
  • Streaming APIs for making data transformations easy

In this chapter, we will look at all these tools in detail. 

Collections

Data is the most important part of data science. When dealing with data, it needs to be efficiently stored and processed, and for this we use data structures. A data structure describes a way to store data efficiently to solve a specific problem, and the Java Collection API is the standard Java API for data structures. This API offers a wide variety of implementations that are useful in practical data science applications.

We will not describe the collection API in full detail, but concentrate on the most useful and important ones--list, set, and map interfaces.

Lists are collections where each element can be accessed by its index. The g0-to implementation of the List interface is...