Book Image

Big Data Analytics with Java

Book Image

Big Data Analytics with Java


Overview of this book

This book covers case studies such as sentiment analysis on a tweet dataset, recommendations on a movielens dataset, customer segmentation on an ecommerce dataset, and graph analysis on actual flights dataset. This book is an end-to-end guide to implement analytics on big data with Java. Java is the de facto language for major big data environments, including Hadoop. This book will teach you how to perform analytics on big data with production-friendly Java. This book basically divided into two sections. The first part is an introduction that will help the readers get acquainted with big data environments, whereas the second part will contain a hardcore discussion on all the concepts in analytics on big data. It will take you from data analysis and data visualization to the core concepts and advantages of machine learning, real-life usage of regression and classification using Naïve Bayes, a deep discussion on the concepts of clustering,and a review of simple neural networks on big data using deepLearning4j or plain Java Spark code. This book is a must-have book for Java developers who want to start learning big data analytics and want to use it in the real world.
Table of Contents (21 chapters)
Big Data Analytics with Java
About the Author
About the Reviewers
Customer Feedback
Free Chapter
Big Data Analytics with Java
Ensembling on Big Data
Real-Time Analytics on Big Data


This is a Java library that is used to build different types of neural networks. It can be easily integrated with Apache Spark on the big data stack and can even run on GPUs. It is the only main Java library out there currently that has a lot of built-in algorithms focusing on deep learning. It also has a very good online community and good documentation, which can be checked on its website at

There are lots of submodules within this Java library and we need some of those sub modules for running our machine learning algorithms. To check out more detail and running samples within Deeplearning4j, please refer to their documentation. We will not cover Deeplearning4j API in this book, please refer to for more information on its documentation.

In order to generate the curiosity of the reader as to what all can be accomplished with deep learning we will end the chapter with another simple sample case study of hand written digit...