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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

Dimensionality reduction and principal component analysis

Alright, time to get all trippy! We're going to talking about higher dimensions, and dimensionality reduction. Sounds scary! There is some fancy math involved, but conceptually it's not as hard to grasp as you might think. So, let's talk about dimensionality reduction and principal component analysis next. Very dramatic sounding! Usually when people talk about this, they're talking about a technique called principal component analysis or PCA, and a specific technique called singular value decomposition or SVD. So PCA and SVD are the topics of this section. Let's dive into it!

Dimensionality reduction

So, what is the curse of dimensionality?...

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