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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 (21) Chapters Close

Big Data Analytics with Java
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
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

Chapter 8. Ensembling on Big Data

Have you used a Kinect while playing video games on Microsoft Xbox? It's so smooth how it detects your motion while you are playing games. It enables users to control and interact with their game without using any external device like a game controller. But how does it do that? How does the device detect the user's motion from the camera and predict the command that the motion suggested? Some users on different forums have claimed that a powerful random forest machine learning algorithm runs behind it and the link for the same is https://www.quora.com/Why-did-Microsoft-decide-to-use-Random-Forests-in-the-Kinect. Though I am myself not sure how true this claim is, this example at least demonstrates at what scale and level this powerful machine learning algorithm has the potential to be used. Random forests are perhaps one of the best machine learning algorithms because of the accuracy they bring in the predicted results and because of their implicit feature...

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