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Hands-On Data Science and Python Machine Learning

You're reading from   Hands-On Data Science and Python Machine Learning Perform data mining and machine learning efficiently using Python and Spark

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787280748
Length 420 pages
Edition 1st Edition
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Author (1):
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Frank Kane Frank Kane
Author Profile Icon Frank Kane
Frank Kane
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Table of Contents (11) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Statistics and Probability Refresher, and Python Practice 3. Matplotlib and Advanced Probability Concepts 4. Predictive Models 5. Machine Learning with Python 6. Recommender Systems 7. More Data Mining and Machine Learning Techniques 8. Dealing with Real-World Data 9. Apache Spark - Machine Learning on Big Data 10. Testing and Experimental Design

Matplotlib and Advanced Probability Concepts

After going through some of the simpler concepts of statistics and probability in the previous chapter, we're now going to turn our attention to some more advanced topics that you'll need to be familiar with to get the most out of the remainder of this book. Don't worry, they're not too complicated. First of all, let's have some fun and look at some of the amazing graphing capabilities of the matplotlib library.

We'll be covering the following topics in this chapter:

  • Using the matplotlib package to plot graphs
  • Understanding covariance and correlation to determine the relationship between data
  • Understanding conditional probability with examples
  • Understanding Bayes' theorem and its importance
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