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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
Languages
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Concepts
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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

Covariance and correlation

Next, we're going to talk about covariance and correlation. Let's say I have two different attributes of something and I want to see if they're actually related to each other or not. This section will give you the mathematical tools you need to do so, and we'll dive into some examples and actually figure out covariance and correlation using Python. These are ways of measuring whether two different attributes are related to each other in a set of data, which can be a very useful thing to find out.

Defining the concepts

Imagine we have a scatter plot, and each one of the data points represents a person that we measured, and we're plotting their age on one axis versus their...

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