Book Image

Java Data Science Cookbook

By : Rushdi Shams
Book Image

Java Data Science Cookbook

By: Rushdi Shams

Overview of this book

If you are looking to build data science models that are good for production, Java has come to the rescue. With the aid of strong libraries such as MLlib, Weka, DL4j, and more, you can efficiently perform all the data science tasks you need to. This unique book provides modern recipes to solve your common and not-so-common data science-related problems. We start with recipes to help you obtain, clean, index, and search data. Then you will learn a variety of techniques to analyze, learn from, and retrieve information from data. You will also understand how to handle big data, learn deeply from data, and visualize data. Finally, you will work through unique recipes that solve your problems while taking data science to production, writing distributed data science applications, and much more - things that will come in handy at work.
Table of Contents (16 chapters)
Java Data Science Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Introduction


Statistical analysis is one of the regular activities of a data scientist. Such analysis includes but is not limited to analysis of descriptive statistics, frequency distributions, simple and multiple regression, correlation and covariance, and statistical significance among data distributions. Luckily, Java has many libraries that are capable of strong statistical analysis of data with only a few lines of coding efforts. This chapter outlines how a data scientist can use Java to make this analysis with 15 recipes.

Note that the focus of this chapter is only on fundamental statistical analysis of data using Java although it is possible use linear algebra, numerical analysis, special functions, complex numbers, geometry, curve fitting, differential equations using the language.

In order to perform the recipes in this chapter, we would require the following:

  1. Apache Commons Math 3.6.1. Therefore, you need to download the JAR file from http://commons.apache.org/proper/commons-math...