Date Lecture Readings Logistics
Th 09/04 Lecture #1 :
Overview of Recommender Systems
[ slides | pynb ]

Th 09/11 Lecture #2 :
Background and baseline methods
[ slides notes | pynb ]

Th 09/18 Lecture #3 :
Machine Learning I
[ slides notes | pynb ]

Th 09/26 Lecture #4 :
Machine Learning II
[ slides notes | pynb ]

Th 09/26 ⏰ Lab Lecture: Run baseline methods in Kaggle

G25 LSB [Kaggle Tutorial]

HW1 out [colab link]
(due Oct 09)

Th 10/09 Lecture #5 :
MF Models I
[ slides notes | pynb ]

Th 10/16 Lecture #6 :
MF Models II
[ slides notes | pynb ]

Th 10/23 ⏰ Kaggle Competition

G25 LSB [Instructions]

Th 10/30 Lecture #7 :
Neural Networks
[ slides notes | pynb ]

HW2 out [colab link]
(due Nov 13)

Th 11/06 No lecture

Th 11/03 Lecture #8 :
Neural Matrix Factorization
[ slides notes | pynb ]

Th 11/20 Lecture #9 :
Neural Recsys with Side Information
[ slides notes | pynb ]

HW3 out [colab link]
(due Dec 04)

Th 11/27 ⏰ Lab Quiz 2: Question sets in Jupyter Notebook

Lab Room: LSB G25 [Final Quiz Instructions]

[Whitelist]