Lecture 19 Quiz
What is NOT a challenge in building Recommender Systems?
Lack of user ratings / only “presence” data
Balancing personalization with generic “good” items
Lack of abundant clickstream data
What is the difference between PCA and Matrix Factorization
They are both equivalent
PCA can be optimized via GPUs, MF cannot be
In PCA, all entries are observed, but not in MF
Which of the following distance or similarity measures was not discussed in class?
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