Java Data Analysis

This is the code repository for Java Data Analysis, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.

About the Book

This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you’ll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression.

In the process, you’ll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs.

By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java.

Instructions and Navigation

All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.

Chapter 1 and the Appendix cover theory and installation steps, they do not have any code files.

The code will look like the following:

Color = {RED, YELLOW, BLUE, GREEN, BROWN, ORANGE}
Surface = {SMOOTH, ROUGH, FUZZY}
Size = {SMALL, MEDIUM, LARGE}

This book is focused on an understanding of the fundamental principles and algorithms used in data analysis. This understanding is developed through the implementation of those principles and algorithms in the Java programming language. Accordingly, the reader should have some experience of programming in Java. Some knowledge of elementary statistics and some experience with database work will also be helpful.

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