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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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Toc

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 era of AI

At the end of the first section of this chapter, we mentioned that we are interested in teaching machines to act intelligently. This task entails the simulation of human intelligence in machines to make them think and act like real humans, but, of course, this is far more than a modest goal. Even from the creation of the first computers in the 1940s, the expectation was that machines would match humans in general intelligence. Back then, there was a great degree of optimism that this could happen in the foreseeable future. These great expectations paved the way for an emerging field called artificial intelligence (AI) that has faced several hype and investment cycles ever since, followed by periods of disappointment in the mid-70s and mid-90s. The great promise of AI has been recorded in myriad science fiction novels and movies. Since then, the high expectations inspired by this vision have not been fully met. Also, the term intelligent is still controversial due to whether...

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