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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

Recommender Systems

Let's talk about my personal area of expertise—recommender systems, so systems that can recommend stuff to people based on what everybody else did. We'll look at some examples of this and a couple of ways to do it. Specifically, two techniques called user-based and item-based collaborative filtering. So, let's dive in.

I spent most of my career at amazon.com and imdb.com, and a lot of what I did there was developing recommender systems; things like people who bought this also bought, or recommended for you, and things that did movie recommendations for people. So, this is something I know a lot about personally, and I hope to share some of that knowledge with you. We'll walk through, step by step, covering the following topics:

  • What are recommender systems?
  • User-based collaborative filtering
  • Item-based collaborative...
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