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Big Data Analytics with Java

You're reading from Big Data Analytics with Java Data analysis, visualization & machine learning techniques

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781787288980

Length 418 pages

Edition 1st Edition

Languages

Java

Tools

Apache Spark

Concepts

Big Data

Author (1):

RAJAT MEHTA

View More author details

Table of Contents (15) Chapters

Preface

1. Big Data Analytics with Java

2. First Steps in Data Analysis FREE CHAPTER

3. Data Visualization

4. Basics of Machine Learning

5. Regression on Big Data

6. Naive Bayes and Sentiment Analysis

7. Decision Trees

8. Ensembling on Big Data

9. Recommendation Systems

10. Clustering and Customer Segmentation on Big Data

11. Massive Graphs on Big Data

12. Real-Time Analytics on Big Data

13. Deep Learning Using Big Data

Index

Chapter 4. Basics of Machine Learning

Any form of any analytical activity depends heavily on the presence of some clues or data. In today's world data is bountifully available. Due to the broad availability of various devices (such as mobile devices), IoT devices, or social network, the amount of data generated day by day is exploding. This data is not all waste; it can be used to make lots of deductions. For example, we can use this data to figure out what particular ad the user might click on next or what item the user might like to purchase along with the item they are already purchasing currently. This data can help us figure out a knowledge base that can directly impact the core business in many useful ways, hence it is very important.

This chapter is action-packed and we will try to cover a lot of ground while learning the basics. In this chapter, we will cover:

Basic concepts of machine learning such as what machine learning is, how it is used, and different forms of...

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Authors (1)

RAJAT MEHTA

RAJAT MEHTA

The author is a VP (Technical Architect) in technology in JP Morgan Chase in New York. The author is a sun certified java developer and has worked on java related technologies for more than 16 years. Current role for the past few years heavily involves the usage of bid data stack and running analytics on it. Author is also a contributor in various open source projects that are available on his GitHub repository and is also a frequent write on dev magazines.

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