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Building Machine Learning Systems with Python

You're reading from   Building Machine Learning Systems with Python Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow

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Product type Paperback
Published in Jul 2018
Publisher
ISBN-13 9781788623223
Length 406 pages
Edition 3rd Edition
Languages
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Authors (3):
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Luis Pedro Coelho Luis Pedro Coelho
Author Profile Icon Luis Pedro Coelho
Luis Pedro Coelho
Willi Richert Willi Richert
Author Profile Icon Willi Richert
Willi Richert
Matthieu Brucher Matthieu Brucher
Author Profile Icon Matthieu Brucher
Matthieu Brucher
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Machine Learning FREE CHAPTER 2. Classifying with Real-World Examples 3. Regression 4. Classification I – Detecting Poor Answers 5. Dimensionality Reduction 6. Clustering – Finding Related Posts 7. Recommendations 8. Artificial Neural Networks and Deep Learning 9. Classification II – Sentiment Analysis 10. Topic Modeling 11. Classification III – Music Genre Classification 12. Computer Vision 13. Reinforcement Learning 14. Bigger Data 15. Where to Learn More About Machine Learning 16. Other Books You May Enjoy

Topic Modeling

In Chapter 6, Clustering - Finding Related Posts, we grouped text documents using clustering. This is a very useful tool, but it is not always the best. Clustering results in each text belonging to exactly one cluster. This book is about machine learning and Python. Should it be grouped with other Python-related works or with machine-related works? In a physical bookstore, we need to choose a single place to stock the book. In an internet store, however, the answer is that this book is about both machine learning and Python, and the book should be listed in both sections. This does not mean that the book will be listed in all sections, of course. We will not list this book with other baking books.

In this chapter, we will learn methods that do not cluster documents into completely separate groups but that allow each document to refer to several topics. These topics...

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