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


Due to the availability of web data, as most of them are in text format, the type of data that a data scientist handles nowadays the most is text. There are many dimensions of text data that can be retrieved from documents, articles, blog posts, social media updates, newswires, and you name it.

Many Java-based tools are available for data scientists to retrieve information from text data. Also, there are tools that achieve a variety of data science tasks. In this chapter, we have limited our scope to a few data science tasks like trivial text feature extractions like sentences and words, document classification using machine learning, topic extraction and modelling, keyword extraction from documents, and named entity recognition.