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Machine Learning Techniques for Text

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

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Product type Paperback
Published in Oct 2022
Publisher Packt
ISBN-13 9781803242385
Length 448 pages
Edition 1st Edition
Languages
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Author (1):
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Nikos Tsourakis Nikos Tsourakis
Author Profile Icon Nikos Tsourakis
Nikos Tsourakis
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Table of Contents (13) Chapters Close

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 12. Other Books You May Enjoy

The language phenomenon

Human language is a structured communication system based on grammar and vocabulary. Although other animals can incorporate some form of communication, human language has a distinctive feature; it is compositional. We can combine or recombine sets of words and create new sentences with little effort. With the odd exception of the waggle dance of honeybees for sharing information about the direction and distance to patches of flowers, no other animal communication system puts messages together like this. Human language is also referential in that we can refer to people, objects, or situations that occurred in the past or could occur in the future. Language’s ability to transmit information about things that aren’t physically or temporally present is unique. Another fascinating characteristic is that it is modality-independent. A spoken language, for instance, uses the auditive modality for communication, while the Braille system used by visually...

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