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How does Netflix recommend movies? In this presentation we go over a very common technique for recommendations called matrix factorization to predict what rating a user will give a movie. It sounds like a complicated mathematical concept, but all it consists of is finding a set of intermediate features such as action, comedy, etc., and using them to help us determine the ratings.
How does Netflix recommend movies? In this presentation we go over a very common technique for recommendations called matrix factorization to predict what rating a user will give a movie. It sounds like a complicated mathematical concept, but all it consists of is finding a set of intermediate features such as action, comedy, etc., and using them to help us determine the ratings.
39.
Matrix
Factorization
2000 x 1000
2M entries
100 x 1000
100K entries
2000 x 100
200K entries
2000 Users
1000
Movies
100 Features
100
Features
2000 Users
1000
Movies
40.
Quiz: How many parameters (arrows)?
20 parameters 18 parameters
41.
2000 users
1000 movies
2000 x 1000 = 2,000,000 parameters
Quiz: How many parameters?
42.
2000 users
1000 movies
300,000 parameters
2000x100 = 200,000 parameters
100 x 1000 = 100,000 parameters
Quiz: How many parameters?
100 features