CS 451 Quiz 25
Low rank matrix factorization, online learning, Map Reduce
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The predictions for a collaborative filtering problem can be written in matrix form as *
1 point
Collaborative filtering for movie predictions results in a matrix of size M x U, where M is the number of movies and U is the number of users. The matrix is "low rank" because *
1 point
To find related movies, we select *
1 point
Why is mean normalization a good idea in collaborative filtering? *
1 point
Online learning algorithms look at each training example only once *
1 point
Online learning algorithm can adapt as user preferences change over time *
1 point
What was mentioned in the video as a useful thing to predict for an online algorithm used for product search? *
1 point
Given multiple machines, Map Reduce allows *
1 point
Map Reduce can be used both with multiple machines and with a single multi-core machine *
1 point
To use Map Reduce to train a neural net using multiple computers, some computers perform forward propagation while other computers perform backpropagation, each on a portion of the training set. *
1 point
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