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Artificial Intelligence with Python

You're reading from   Artificial Intelligence with Python A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781786464392
Length 446 pages
Edition 1st Edition
Languages
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Author (1):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Introduction to Artificial Intelligence FREE CHAPTER 2. Classification and Regression Using Supervised Learning 3. Predictive Analytics with Ensemble Learning 4. Detecting Patterns with Unsupervised Learning 5. Building Recommender Systems 6. Logic Programming 7. Heuristic Search Techniques 8. Genetic Algorithms 9. Building Games With Artificial Intelligence 10. Natural Language Processing 11. Probabilistic Reasoning for Sequential Data 12. Building A Speech Recognizer 13. Object Detection and Tracking 14. Artificial Neural Networks 15. Reinforcement Learning 16. Deep Learning with Convolutional Neural Networks

Chapter 5. Building Recommender Systems

In this chapter, we are going to learn how to build a movie recommendation system. We will discuss how to create a training pipeline that can be trained with custom parameters. We will then learn about the Nearest Neighbors classifier and see how to implement it. We use these concepts to discuss collaborative filtering and then use it to build a recommender system.

By the end of this chapter, you will learn about the following:

  • Creating a training pipeline
  • Extracting the nearest neighbors
  • Building a K Nearest Neighbors classifier
  • Computing similarity scores
  • Finding similar users using collaborative filtering
  • Building a movie recommendation system
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