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R Machine Learning Projects

You're reading from   R Machine Learning Projects Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789807943
Length 334 pages
Edition 1st Edition
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Author (1):
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Dr. Sunil Kumar Chinnamgari Dr. Sunil Kumar Chinnamgari
Author Profile Icon Dr. Sunil Kumar Chinnamgari
Dr. Sunil Kumar Chinnamgari
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Table of Contents (12) Chapters Close

Preface 1. Exploring the Machine Learning Landscape FREE CHAPTER 2. Predicting Employee Attrition Using Ensemble Models 3. Implementing a Jokes Recommendation Engine 4. Sentiment Analysis of Amazon Reviews with NLP 5. Customer Segmentation Using Wholesale Data 6. Image Recognition Using Deep Neural Networks 7. Credit Card Fraud Detection Using Autoencoders 8. Automatic Prose Generation with Recurrent Neural Networks 9. Winning the Casino Slot Machines with Reinforcement Learning 10. The Road Ahead
11. Other Books You May Enjoy

The Road Ahead

Congratulations on reaching this point in the book! It has been an exciting journey for me, writing the various chapters and implementing the projects. I learned quite a lot as a result of undertaking this journey and I hope your experience has been the same.

Finally, here we are at the concluding chapter!

The year 2018 can be considered a boom year for data science, machine learning (ML), and artificial intelligence (AI). Just look at the number of start-ups with the terms ML and AI in their tag lines, the focal points for acquisitions on the part of big companies, and the topics at the biggest tech conferences. It does not take a long time for us to realize that data, ML, and AI are omnipresent, and I believe that this trend is going to continue for a few years to come. More and more industries are going to utilize ML and AI in a big way. This essentially is going...

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