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Practical Big Data Analytics

You're reading from   Practical Big Data Analytics Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781783554393
Length 412 pages
Edition 1st Edition
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Author (1):
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Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
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Table of Contents (13) Chapters Close

Preface 1. Too Big or Not Too Big FREE CHAPTER 2. Big Data Mining for the Masses 3. The Analytics Toolkit 4. Big Data With Hadoop 5. Big Data Mining with NoSQL 6. Spark for Big Data Analytics 7. An Introduction to Machine Learning Concepts 8. Machine Learning Deep Dive 9. Enterprise Data Science 10. Closing Thoughts on Big Data 11. External Data Science Resources 12. Other Books You May Enjoy

Summary

Big data is undoubtedly a vast subject that can seem overly complex at first sight. Practice makes perfect, and so it is with the study of big data--the more you get involved, the more familiar the topics and verbiage gets, and the more comfortable the subject becomes.

A keen study of the various dimensions of the topic of big data analytics will help you develop an intuitive sense of the subject. This book aims to provide a holistic overview of the topic and will cover a broad range of areas such as Hadoop, Spark, NoSQL databases as well as topics that are based on hardware design and cloud infrastructures. In the next chapter, we will introduce the concept of Big Data Mining and discuss about the technical elements as well as the selection criteria for Big Data technologies.

You have been reading a chapter from
Practical Big Data Analytics
Published in: Jan 2018
Publisher: Packt
ISBN-13: 9781783554393
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