| 1 |
Introduction |
Lecture 1 |
| 2 |
Recommender System Types |
Lecture 2 |
| 3 |
SVD and similarity metrics |
Lecture 3 |
| 4 |
Matrix Factorization and completion |
Lecture 4 |
| 6 |
SGD and Matrix Completion |
Lecture 6 |
| 7 |
Auto Grad and Auto Encoders |
Lecture 7 |
| 8 |
MLP for Product Recs |
Lecture 8 |
| 9 |
News Recommendations Case Study |
Lecture 9 |
| 10 |
Ranking and Recommendations |
Lecture 10 |
| 11 |
Ranking metrics |
Lecture 11 |
| 12 |
Ranking Loss Functions |
[Lecture 12] (Lectures/Lecture_12_annotated.pdf) |
| 13 |
Course Wrap Up |
[Lecture 13] (Lectures/Lecture_13_annotated.pdf) |