Download e-book for iPad: Big Data Analytics with Java by Rajat Mehta

Key Features

• Acquire real-world set of instruments for development company point info technological know-how applications
• Surpasses the barrier of alternative languages in facts technology and examine create beneficial object-oriented codes
• Extensive use of Java compliant colossal info instruments like apache spark, Hadoop, etc.

Book Description

This publication covers case stories akin to sentiment research on a tweet dataset, tips on a movielens dataset, purchaser segmentation on an ecommerce dataset, and graph research on real flights dataset.

This e-book is an end-to-end consultant to enforce analytics on monstrous information with Java. Java is the de facto language for significant giant info environments, together with Hadoop. This booklet will educate you the way to accomplish analytics on sizeable info with production-friendly Java. This booklet primarily divided into sections. the 1st half is an advent that may support the readers get familiar with huge facts environments, while the second one half will include a hardcore dialogue on all of the recommendations in analytics on tremendous info. it is going to take you from facts research and information visualization to the middle techniques and merits of computer studying, real-life utilization of regression and type utilizing Naive Bayes, a deep dialogue at the suggestions of clustering,and a overview of easy neural networks on giant facts utilizing deepLearning4j or simple Java Spark code. This e-book is a must have booklet for Java builders who are looking to commence studying colossal facts analytics and need to exploit it within the actual world.

What you'll learn

• Start from easy analytic projects on significant data
• Get into extra complicated initiatives with predictive analytics on giant facts utilizing computing device learning
• Learn genuine time analytic tasks
• Understand the recommendations with examples and case studies
• Prepare and refine info for analysis
• Create charts to be able to comprehend the data
• See a variety of real-world datasets

About the Author

The writer is a vice president (Technical Architect) in know-how in JP Morgan Chase in manhattan. the writer is a sunlight qualified java developer and has labored on java comparable applied sciences for greater than sixteen years. present function for the previous few years seriously comprises the use of bid facts stack and operating analytics on it. writer can be a contributor in a variety of open resource tasks which are on hand on his GitHub repository and can also be a widespread write on dev magazines.

Table of Contents

1. Big information Analytics with Java
2. First Steps on facts Analysis
3. Data Visualization
4. Basics of computing device Learning
5. Regression on tremendous Data
6. Naive Bayes and Sentiment Analysis
7. Classification utilizing selection Trees
8. Classification on ensemble of selection Trees
9. Recommendations on substantial Data
10. Clustering in motion on sizeable Data
11. Building graphs on huge Data
12. Streaming on enormous Data
13. Deep studying utilizing titanic Data