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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

More Data Mining and Machine Learning Techniques

In this chapter, we talk about a few more data mining and machine learning techniques. We will talk about a really simple technique called k-nearest neighbors (KNN). We'll then use KNN to predict a rating for a movie. After that, we'll go on to talk about dimensionality reduction and principal component analysis. We'll also look at an example of PCA where we will reduce 4D data to two dimensions while still preserving its variance.

We'll then walk through the concept of data warehousing and see the advantages of the newer ELT process over the ETL process. We'll learn the fun concept of reinforcement learning and see the technique used behind the intelligent Pac-Man agent of the Pac-Man game. Lastly, we'll see some fancy terminology used for reinforcement learning.

We'll cover the following topics...

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