English | 2017 | ISBN: 1787285651 | 412 Pages | EPUB, AZW3, PDF (conv) | 52 MB
Get the most out of the popular Java libraries and tools to perform efficient data analysis
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks.
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.
What You Will Learn
- Develop Java programs that analyze data sets of nearly any size, including text
- Implement important machine learning algorithms such as regression, classification, and clustering
- Interface with and apply standard open source Java libraries and APIs to analyze and visualize data
- Process data from both relational and non-relational databases and from time-series data
- Employ Java tools to visualize data in various forms
- Understand multimedia data analysis algorithms and implement them in Java.