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You're reading from Python Machine Learning By Example The easiest way to get into machine learning

Product type Paperback

Published in May 2017

Publisher Packt

ISBN-13 9781783553112

Length 254 pages

Edition 1st Edition

Languages

Python

Tools

Matplotlib

Concepts

Machine Learning

Authors (2):

Yuxi (Hayden) Liu

Ivan Idris

View More author details

Table of Contents (9) Chapters

Preface

1. Getting Started with Python and Machine Learning FREE CHAPTER

2. Exploring the 20 Newsgroups Dataset with Text Analysis Algorithms

3. Spam Email Detection with Naive Bayes

4. News Topic Classification with Support Vector Machine

5. Click-Through Prediction with Tree-Based Algorithms

6. Click-Through Prediction with Logistic Regression

7. Stock Price Prediction with Regression Algorithms

8. Best Practices

Troubleshooting and asking for help

Currently the best forum is at http://stackoverflow.com. You can also reach out on mailing lists or IRC chat. The following is a list of mailing lists:

Scikit-learn: https://lists.sourceforge.net/lists/listinfo/scikit-learn-general.
NumPy and SciPy mailing list: https://www.scipy.org/scipylib/mailing-lists.html.

IRC channels:

#scikit-learn @ freenode
#scipy @ freenode

You have been reading a chapter from

Python Machine Learning By Example

Published in: May 2017

Publisher: Packt

ISBN-13: 9781783553112

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Authors (2)

Idris

Ivan Idris has an MSc in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a Java developer, data warehouse developer, and QA analyst. His main professional interests are business intelligence, big data, and cloud computing. Ivan Idris enjoys writing clean, testable code and interesting technical articles. Ivan Idris is the author of NumPy 1.5. Beginner's Guide and NumPy Cookbook by Packt Publishing.

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Yuxi (Hayden) Liu

Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.

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