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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

Fetching the data

Luckily for us, the team behind StackOverflow provides most of the data behind the StackExchange universe to which StackOverflow belongs under a cc-by-sa license. At the time of writing this book, the latest data dump can be found at https://archive.org/download/stackexchange. It contains data dumps of all the Q&A sites of the StackExchange family. For StackOverflow, you will find multiple files, of which we only need the stackoverflow.com-Posts.7z file, which is 11.3 GB.

After downloading and extracting it, we have around 59 GB of data in the XML format, containing all questions and answers as individual row tags within the root tag posts:

<?xml version="1.0" encoding="utf-8"?>
<posts>
...
<row Id="4572748" PostTypeId="2" ParentId="4568987" CreationDate="2011-01-01T00:01:03.387" Score...
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