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

What is machine learning?

Machine learning is a form of artificial intelligence where a computer program learns from the data it is fed or trained with. After learning from this data it internally builds a knowledge base of rules and based on this knowledge base it can later make predictions when it is fed new data. Machine learning is part AI, part data mining, and part statistics, but overall the criterion is to teach a machine to make new decisions based on past data it is trained with. So, for example, if we teach a machine some data regarding the inventory statistics of a store throughout the year then you might be able to tell things such as in which months the items sell more or which items sell more often. Also, it can tell the shop owner if they are selling one particular item more than other items; it can also show this to the customer so as to increase sales.

The concept of making new predictions is very important as we can now make predictions such as in which zone or area a marketing...