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


Deep learning is simply neural networks with multiple layers. It is also known as deep neural network learning or unsupervised feature learning. The author believes that deep learning will become the next accomplice of machine learning practitioners and data scientists because of its ability to solve real-world data problems.

Deep Learning for Java (DL4j) is an open-source, distributed Java library for deep learning for JVM. It comes with other libraries, as follows:

  • Deeplearning4J: Neural Net Platform

  • ND4J: NumPy for the JVM

  • DataVec: Tool for machine learning ETL operations

  • JavaCPP: The bridge between Java and native C++

  • Arbiter: Evaluation tool for machine learning algorithms

  • RL4J: Deep reinforcement learning for the JVM

However, we will be focusing on a few key recipes for DL4j only, given the scope of this book. To be specific, we will be discussing recipes to use Word2vec algorithm and their use for real-world NLP and information retrieval problem, deep belief neural networks...