You're reading from Machine Learning Techniques for Text Apply modern techniques with Python for text processing, dimensionality reduction, classification, and evaluation

Product type Paperback

Published in Oct 2022

Publisher Packt

ISBN-13 9781803242385

Length 448 pages

Edition 1st Edition

Languages

Python

Concepts

Machine Learning

Author (1):

Nikos Tsourakis

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Table of Contents (13) Chapters

Preface

1. Chapter 1: Introducing Machine Learning for Text

2. Chapter 2: Detecting Spam Emails FREE CHAPTER

3. Chapter 3: Classifying Topics of Newsgroup Posts

4. Chapter 4: Extracting Sentiments from Product Reviews

5. Chapter 5: Recommending Music Titles

6. Chapter 6: Teaching Machines to Translate

7. Chapter 7: Summarizing Wikipedia Articles

8. Chapter 8: Detecting Hateful and Offensive Language

9. Chapter 9: Generating Text in Chatbots

10. Chapter 10: Clustering Speech-to-Text Transcriptions

11. Index

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Technical requirements

The chapter’s code has been truncated in certain parts to facilitate reading the content. However, the whole code is available as different Jupyter notebooks in the book’s GitHub repository:

https://github.com/PacktPublishing/Machine-Learning-Techniques-for-Text/tree/main/chapter-10.

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You're reading from Machine Learning Techniques for Text Apply modern techniques with Python for text processing, dimensionality reduction, classification, and evaluation

Table of Contents (13) Chapters

Technical requirements

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Authors (1)