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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

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

abstractive summarization 263

attention mechanism 277, 279

performing 277

transformers 280

transformers, implementing 288

accuracy 54

activation function 153

activation map 336

Adaptive Boosting (AdaBoost) 314-316

agglomerative clustering 398

application programming interface (API) 159

Area Under the ROC Curve (AUC) 59

creating 59, 60

artificial general intelligence (AGI) 4

artificial intelligence (AI) 3, 4

research fields 5-7

artificial narrow intelligence (ANI) 4

artificial neural network (ANN)

creating 154, 155

training 156-159

artificial neuron 153, 154

artificial superintelligence (ASI) 4

association analysis 12

attention mechanism 277, 279

autoencoders 206, 207

autoencoding 346

autoregressive 346

B

backpropagation...

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