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
About the Author
About the Reviewer
Customer Feedback


In this chapter and the following, chapter we will cover recipes that use machine-learning techniques to learn patterns from data. These patterns are the center of attention for at least three key machine-learning tasks: classification, regression, and clustering. Classification is the task of predicting a value from a nominal class. In contrast to classification, regression models attempt to predict a value from a numeric class. Finally, clustering is the technique of grouping of data points based on their proximity.

There are many Java-based tools, workbenches, libraries, and APIs that can be used for research and development in the areas of machine learning mentioned earlier. One of the most popular tools is Waikato Environment of Knowledge Analysis (Weka), which is a free software licensed under the GNU General Public License. It is written in Java and has a very good collection of data preparation and filtering options, classical machine learning algorithms with customizable...