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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

Generating Text in Chatbots

Cutting-edge artificial intelligence applications can now produce uncannily humanlike creations, from written essays to music and drawings. These applications are a great promise toward artificial general intelligence, to the point where machines understand or learn any intellectual task that humans can perform. Unhindered conversation with a machine has always been at the forefront of this vision. Interestingly, the most common depiction of machine intelligence in popular culture is conversational agents that can mimic human dialogs. In this chapter, we will deal with a particular type: chatbots.

Chatbots have received much hype in recent years; in this chapter, we will discuss related topics from the perspective of natural language generation. Particular emphasis is given to language modeling, which is an integral part of modern chatbot deployments. First, we will look deeper at this core component of modern natural language processing and contrast...

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