This slide is a part of Introduction to Machine Learning course by Code Heroku. Here is the recorded version of our Building a movie recommendation engine tutorial: https://www.youtube.com/watch?v=XoTwndOgXBM Here is the Medium post for this lesson: https://medium.com/code-heroku/building-a-movie-recommendation-engine-in-python-using-scikit-learn-c7489d7cb145 Here is the link to Introduction to Machine Learning Course: http://www.codeheroku.com/course?course_id=1 You can watch all our upcoming and past workshops here: http://www.codeheroku.com Subscribe to our YouTube channel: https://www.youtube.com/channel/UCL-_0RrZ3084Ea8Yavtcd9g Follow our publication on Medium: https://medium.com/code-heroku Visit our Facebook page: https://www.facebook.com/codeheroku

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2. Mihir Thakkar
Founder and Instructor
hello@codeheroku.com
Building a Movie
Recommendation
Engine

3. SESSION
OBJECTIVES
● Quick Recap
● Recommendation
Systems
● Revise Some Math
● Build it!

4. www.codeheroku.com Building a Movie Recommendation Engine
Machine Learning Pipeline
Data Extraction
and Cleaning
Build ML
Model
Build Software
Infrastructure

5. www.codeheroku.com Building a Movie Recommendation Engine
Supervised Machine Learning
House Size (Sq feet) Location Age (years) Prize (Lakh
Rs)
500 Mumbai 2 70
1500 Pune 3 100
2000 Banglore 4 60
1000 Mumbai 2 ?
3000 Pune 10 ?
Training Data
Test Data
Features

6. www.codeheroku.com Building a Movie Recommendation Engine
2. Netflix1. Amazon
What’s Common?

7. QUIZ
Who are the Users and Items for RE in the following platforms?
1. LinkedIn
2. Amazon
3. Netflix
4. Facebook
Users: Members; Items: Members
Users: Members; Items: Products (E.g. Books, Electronics)
Users: Members; Items: Movie
Users: Members; Items: Members

8. www.codeheroku.com Building a Movie Recommendation Engine
Implementing A Recommender System
1. Popularity / Rating Based System

9. www.codeheroku.com Building a Movie Recommendation Engine
Implementing A Recommender System
3. Collaborative Filtering2. Content Based

10. www.codeheroku.com Building a Movie Recommendation Engine
Similarity Between Content
Text A: London Paris London
Text B: Paris Paris London

11. www.codeheroku.com Building a Movie Recommendation Engine
Paris
London0 1 2 3 4
5
4
3
2
1
Text A: London Paris London (London: 2, Paris: 1)
Text B: Paris Paris London (London: 1, Paris: 2)
Distance Between Two Vectors
(1,2)
(2,1)
D

12. www.codeheroku.com Building a Movie Recommendation Engine
When To Use Angular Distance?

13. www.codeheroku.com Building a Movie Recommendation Engine
Quiz
In which of the following scenarios you are most likely to use Cosine
Similarity measure?
1. Determining gender based on shoe length, height, weight etc.
2. Comparing similarities between documents of uneven size
3. Predicting rainfall based on city location, temperature, humidity etc.

14. www.codeheroku.com Building a Movie Recommendation Engine
Quiz Given the similarity matrix below, which movie is most
similar to Movie 0 ?

15. www.codeheroku.com Building a Movie Recommendation Engine
Let’s Build It
http://codeheroku.com/static/workshop/datasets/movie_recommender.zip
http://www.codeheroku.com/static/workshop/hw/movie_recommendation/assignment.pdf

16. www.codeheroku.com Building a Movie Recommendation Engine

17. www.codeheroku.com Building a Movie Recommendation Engine
Thank you!

18. www.codeheroku.com Building a Movie Recommendation Engine
Alternative Links:
DataSet: https://drive.google.com/file/d/1sJ9N2T2zDQwvywHCC6RCO68olL97Mp4O/view?usp=sharing
Assignment: https://drive.google.com/file/d/1EKjBr0id9_HtzGJzrNs8yGZ5MWWExx-b/view?usp=sharing

19. www.codeheroku.com Building a Movie Recommendation Engine
Recommendation Systems
Users Items