Book description
Examine the techniques and Java tools supporting the growing field of data science
About This Book
 Your entry ticket to the world of data science with the stability and power of Java
 Explore, analyse, and visualize your data effectively using easytofollow examples
 Make your Java applications more capable using machine learning
Who This Book Is For
This book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful.
What You Will Learn
 Understand the nature and key concepts used in the field of data science
 Grasp how data is collected, cleaned, and processed
 Become comfortable with key data analysis techniques
 See specialized analysis techniques centered on machine learning
 Master the effective visualization of your data
 Work with the Java APIs and techniques used to perform data analysis
In Detail
Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application.
The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation.
The final chapter illustrates an indepth data science problem and provides a comprehensive, Javabased solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book.
Style and approach
This book follows a tutorial approach, providing examples of each of the major concepts covered.
With a stepbystep instructional style, this book covers various facets of data science and will get you up and running quickly.
Publisher resources
Table of contents

Java for Data Science
 Java for Data Science
 Credits
 About the Authors
 About the Reviewers
 www.PacktPub.com
 Customer Feedback
 Preface

1. Getting Started with Data Science
 Problems solved using data science
 Understanding the data science problem  solving approach
 Acquiring data for an application
 The importance and process of cleaning data
 Visualizing data to enhance understanding
 The use of statistical methods in data science
 Machine learning applied to data science
 Using neural networks in data science
 Deep learning approaches
 Performing text analysis
 Visual and audio analysis
 Improving application performance using parallel techniques
 Assembling the pieces
 Summary
 2. Data Acquisition
 3. Data Cleaning
 4. Data Visualization
 5. Statistical Data Analysis Techniques
 6. Machine Learning
 7. Neural Networks
 8. Deep Learning
 9. Text Analysis
 10. Visual and Audio Analysis
 11. Mathematical and Parallel Techniques for Data Analysis
 12. Bringing It All Together
Product information
 Title: Java for Data Science
 Author(s):
 Release date: January 2017
 Publisher(s): Packt Publishing
 ISBN: 9781785280115
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