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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

Sentiment Analysis of Amazon Reviews with NLP

Every day, we generate data from emails, online posts such as blogs, social media comments, and more. It is not surprising to say that unstructured text data is much larger in size than the tabular data that exists in the databases of any organization. It is important for organizations to acquire useful insights from the text data pertaining to the organization. Due to the different nature of the text data when compared to data in databases, the methods that need to be employed to understand the text data are different. In this chapter, we will learn a number of key techniques in natural language processing (NLP) that help us to work on text data.

The common definition of NLP is as follows: an area of computer science and artificial intelligence that deals with the interactions between computers and human (natural) languages; in particular...

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