Big Data Analytics with Java by Rajat Mehta PDF

By Rajat Mehta

Key Features

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

Book Description

This e-book covers case reviews reminiscent of 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 advisor to enforce analytics on enormous info with Java. Java is the de facto language for significant huge facts environments, together with Hadoop. This ebook will train you the way to accomplish analytics on massive information with production-friendly Java. This publication essentially divided into sections. the 1st half is an advent that would support the readers get accustomed to significant information environments, while the second one half will comprise a hardcore dialogue on all of the strategies in analytics on significant info. it's going to take you from facts research and information visualization to the center options and benefits of laptop studying, real-life utilization of regression and category utilizing Naive Bayes, a deep dialogue at the strategies of clustering,and a assessment of straightforward neural networks on enormous facts utilizing deepLearning4j or undeniable Java Spark code. This e-book is a must have booklet for Java builders who are looking to commence studying massive information analytics and wish to take advantage of it within the actual world.

What you'll learn

  • Start from basic analytic projects on tremendous data
  • Get into extra advanced initiatives with predictive analytics on tremendous info utilizing computer learning
  • Learn actual time analytic tasks
  • Understand the innovations with examples and case studies
  • Prepare and refine facts for analysis
  • Create charts so that it will comprehend the data
  • See a variety of real-world datasets

About the Author

The writer is a vice chairman (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 position for the prior few years seriously comprises the use of bid facts stack and working analytics on it. writer can be a contributor in quite a few open resource tasks which are on hand on his GitHub repository and can also be a common write on dev magazines.

Table of Contents

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

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