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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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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

Bayesian methods - Concepts

Did you ever wonder how the spam classifier in your e-mail works? How does it know that an e-mail might be spam or not? Well, one popular technique is something called Naive Bayes, and that's an example of a Bayesian method. Let's learn more about how that works. Let's discuss Bayesian methods.

We did talk about Bayes' theorem earlier in this book in the context of talking about how things like drug tests could be very misleading in their results. But you can actually apply the same Bayes' theorem to larger problems, like spam classifiers. So let's dive into how that might work, it's called a Bayesian method.

So just a refresher on Bayes' theorem -remember, the probability of A given B is equal to the overall probability of A times the probability of B given A over the overall probability of B:

How can we use...

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