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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

Implementing a Jokes Recommendation Engine

I am sure this is something you have experienced as well: while shopping for a cellphone on Amazon, you are also shown some product recommendations of mobile accessories, such as screen guards and phone cases. Not very surprisingly, most of us end up buying one or more of these recommendations! The primary purpose of a recommendation engine in an e-commerce site is to lure buyers into purchasing more from vendors. Of course, this is no different from a salesperson trying to up-sell or cross-sell to customers in a physical store.

You may recollect the Customers Who Bought This Item Also Bought This heading on Amazon (or any e-commerce site) where recommendations are shown. The aim of these recommendations is to get you to buy not just one product but a product combo, therefore pushing the sales revenues in an upward direction. Recommendations...

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