Schedule
| Date | Lecture | Readings | Logistics | |
|---|---|---|---|---|
| Th 09/04 |
Lecture #1
:
Overview of Recommender Systems [ slides | pynb ] |
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| Th 09/11 |
Lecture #2
:
Background and baseline methods [ slides notes | pynb ] |
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| Th 09/18 |
Lecture #3
:
Machine Learning I [ slides notes | pynb ] |
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| Th 09/26 |
Lecture #4
:
Machine Learning II [ slides notes | pynb ] |
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| Th 09/26 |
⏰ Lab Lecture: Run baseline methods in Kaggle G25 LSB [Kaggle Tutorial] HW1 out [colab link] |
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| Th 10/09 |
Lecture #5
:
MF Models I [ slides notes | pynb ] |
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| Th 10/16 |
Lecture #6
:
MF Models II [ slides notes | pynb ] |
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| Th 10/23 |
⏰ Kaggle Competition G25 LSB [Instructions] |
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| Th 10/30 |
Lecture #7
:
Neural Networks [ slides notes | pynb ] |
HW2 out [colab link] |
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| Th 11/06 |
No lecture |
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| Th 11/03 |
Lecture #8
:
Neural Matrix Factorization [ slides notes | pynb ] |
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| Th 11/20 |
Lecture #9
:
Neural Recsys with Side Information [ slides notes | pynb ] |
HW3 out [colab link] |
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| Th 11/27 |
⏰ Lab Quiz 2: Question sets in Jupyter Notebook Lab Room: LSB G25 [Final Quiz Instructions] |
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