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Raspberry Pi 3 Cookbook for Python Programmers

You're reading from   Raspberry Pi 3 Cookbook for Python Programmers Unleash the potential of Raspberry Pi 3 with over 100 recipes

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Product type Paperback
Published in Apr 2018
Publisher
ISBN-13 9781788629874
Length 552 pages
Edition 3rd Edition
Languages
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Authors (2):
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Steven Lawrence Fernandes Steven Lawrence Fernandes
Author Profile Icon Steven Lawrence Fernandes
Steven Lawrence Fernandes
Tim Cox Tim Cox
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Tim Cox
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with a Raspberry Pi 3 Computer 2. Dividing Text Data and Building Text Classifiers FREE CHAPTER 3. Using Python for Automation and Productivity 4. Predicting Sentiments in Words 5. Creating Games and Graphics 6. Detecting Edges and Contours in Images 7. Creating 3D Graphics 8. Building Face Detector and Face Recognition Applications 9. Using Python to Drive Hardware 10. Sensing and Displaying Real-World Data 11. Building Neural Network Modules for Optical Character Recognition 12. Building Robots 13. Interfacing with Technology 14. Can I Recommend a Movie for You? 15. Hardware and Software List 16. Other Books You May Enjoy

Developing a movie recommendation module

We are now ready to build the movie recommendation engine. We will use all the functionalities that we built in the previous recipes. Let's see how it can be done.

How to do it...

  1. We will create a new Python file and import the following packages:
import json 
import numpy as np 
from euclidean_score import euclidean_score 
from pearson_score import pearson_score 
from search_similar_user import search_similar_user
  1. For movie recommendations for a given user, we will define a function first. We now check whether the user already exists:
# Generate recommendations for a given user 
def recommendation_generated(dataset, user): 
if user not in dataset: 
raiseTypeError('User...
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