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Python Machine Learning Cookbook

You're reading from   Python Machine Learning Cookbook Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789808452
Length 642 pages
Edition 2nd Edition
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Authors (2):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
Prateek Joshi Prateek Joshi
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Prateek Joshi
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Toc

Table of Contents (18) Chapters Close

Preface 1. The Realm of Supervised Learning FREE CHAPTER 2. Constructing a Classifier 3. Predictive Modeling 4. Clustering with Unsupervised Learning 5. Visualizing Data 6. Building Recommendation Engines 7. Analyzing Text Data 8. Speech Recognition 9. Dissecting Time Series and Sequential Data 10. Analyzing Image Content 11. Biometric Face Recognition 12. Reinforcement Learning Techniques 13. Deep Neural Networks 14. Unsupervised Representation Learning 15. Automated Machine Learning and Transfer Learning 16. Unlocking Production Issues 17. Other Books You May Enjoy

Analyzing the sentiment of a sentence

Sentiment analysis is one of the most popular applications of NLP. Sentiment analysis refers to the process of determining whether a given piece of text is positive or negative. In some variations, we consider neutral as a third option. This technique is commonly used to discover how people feel about a particular topic. This is used to analyze the sentiments of users in various forms, such as marketing campaigns, social media, e-commerce, and so on.

Getting ready

In this recipe, we will analyze the sentiment of a sentence by using a Naive Bayes classifier, starting with the data contained in the movie_reviews corpus.

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