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Big Data Analytics with Java

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

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787288980
Length 418 pages
Edition 1st Edition
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Author (1):
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RAJAT MEHTA RAJAT MEHTA
Author Profile Icon RAJAT MEHTA
RAJAT MEHTA
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Table of Contents (15) Chapters Close

Preface 1. Big Data Analytics with Java FREE CHAPTER 2. First Steps in Data Analysis 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

Summary

We started this chapter on a simple note by going over the very basic yet very power simple analytics on simple datasets. While doing so, we also learned a very powerful module of Apache Spark called Spark SQL. Using this module, Java developers can use their regular SQL skills and analyze their big data datasets.

After exploring the simple analytics piece using spark-sql, we went over two complex analytic algorithms: Apriori and FP-Growth. We learned how we can use these algorithms to build association rules from a transaction dataset.

In the next chapter, we will learn the basics of machine learning and get an introduction to the machine learning approach for dealing with a predictive analytics problem.

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