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Python Machine Learning Cookbook, - Second Edition

You're reading from  Python Machine Learning Cookbook, - Second Edition

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789808452
Pages 642 pages
Edition 2nd Edition
Languages
Authors (2):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
View More author details
Toc

Table of Contents (18) Chapters close

Preface 1. The Realm of Supervised Learning 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

Introduction

Text analysis and natural language processing (NLP) are an integral part of modern artificial intelligence systems. Computers are good at understanding rigidly structured data with limited variety. However, when we deal with unstructured, free-form text, things begin to get difficult. Developing NLP applications is challenging because computers have a hard time understanding the underlying concepts. There are also many subtle variations to the way that we communicate things. These can be in the form of dialects, context, slang, and so on.

In order to solve this problem, NLP applications are developed based on machine learning. These algorithms detect patterns in text data so that we can extract insights from them. Artificial intelligence companies make heavy use of NLP and text analysis in order to deliver relevant results. Some of the most common applications of...

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