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Python Machine Learning Cookbook, - Second Edition

You're reading from  Python Machine Learning Cookbook, - Second Edition

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789808452
Pages 642 pages
Edition 2nd Edition
Languages
Authors (2):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
View More author details
Toc

Table of Contents (18) Chapters close

Preface 1. The Realm of Supervised Learning 2. Constructing a Classifier 3. Predictive Modeling 4. Clustering with Unsupervised Learning 5. Visualizing Data 6. Building Recommendation Engines 7. Analyzing Text Data 8. Speech Recognition 9. Dissecting Time Series and Sequential Data 10. Analyzing Image Content 11. Biometric Face Recognition 12. Reinforcement Learning Techniques 13. Deep Neural Networks 14. Unsupervised Representation Learning 15. Automated Machine Learning and Transfer Learning 16. Unlocking Production Issues 17. Other Books You May Enjoy

Generating movie recommendations

In this recipe, we will generate movie recommendations.

Getting ready

In this recipe, we will use all the functionality that we built in the previous recipes to build a movie recommendation engine. Let's take a look at how to build it.

How to do it...

Let's take a look at how to generate movie recommendations:

  1. Create a new Python file and import the following packages (the full code is in the movie_recommendations.py file that's already provided for you):
import json 
import numpy as np 
 
from pearson_score import pearson_score...
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