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Python: Deeper Insights into Machine Learning

You're reading from   Python: Deeper Insights into Machine Learning Deeper Insights into Machine Learning

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Product type Course
Published in Aug 2016
Publisher Packt
ISBN-13 9781787128576
Length 901 pages
Edition 1st Edition
Languages
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Authors (3):
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John Hearty John Hearty
Author Profile Icon John Hearty
John Hearty
Sebastian Raschka Sebastian Raschka
Author Profile Icon Sebastian Raschka
Sebastian Raschka
David Julian David Julian
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David Julian
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Toc

Table of Contents (6) Chapters Close

Preface 1. Module 1 FREE CHAPTER 2. Module 2 3. Module 3 A. Biblography
Index

Chapter 10. Chapter Code Requirements

This book's content leverages openly available data and code, including open source Python libraries and frameworks. While each chapter's example code is accompanied by a README file documenting all the libraries required to run the code provided in that chapter's accompanying scripts, the content of these files is collated here for your convenience.

It is recommended that you already have some libraries that are required for the earlier chapters when working with code from any later chapter. These requirements are identified using keywords. It is particularly important to set up the libraries mentioned in Chapter 1, Unsupervised Machine Learning, for any content provided later in the book. The requirements for every chapter are given in the following table:

Chapter Number

Requirements

1

  • Python 3 (3.4 recommended)
  • sklearn (NumPy, SciPy)
  • matplotlib

2-4

  • theano

5

  • Semisup-learn

6

  • Natural Language Toolkit (NLTK)
  • BeautifulSoup...
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