JSC370 and JSC470: Data Science II and III
Winter 2021
Where and When
- Instructor: David Duvenaud
- Teaching Assistant: harsh Panchal
- Email: duvenaud@cs.toronto.edu, please put “JSC370” or “JSC470” in the title.
- Location: Zoom (see Quercus for details)
- Time: Tuesday and Thursdays, 3-5pm
- Office hours: Wednesdays 4-5 by zoom.
- Course Forum: Discourse
- Course syllabus
Course Structure
Tentative Schedule
Week 1: Background, motivation, course setup
January 12 Lecture: Video | Slides
- We don’t need data scientists, we need data engineers
- Data Science Subreddit - Has great discussion of what jobs are available, career trajectories and considerations, common problems, etc.
January 12 Tutorial: Review of Python, Numpy, Pandas, Git, Colab Video
Week 2
| January 19: Guest Lecture: Ben Allison, Principal Machine Learning Scientist at Amazon | Video |
January 21: Lecture on Latent variable models and collaborative filtering, intro to Assignment 1
-
Slides Video - Intro to JAX
- Collaborative Filtering and the Missing at Random Assumption
- If It’s Worth Doing, It’s Worth Doing With Made-Up Statistics
- Intro to probabilistic matrix factorization
Week 3
| January 25: Lecture 3: Confounding, censoring, and assignment 1 lab. Video | Assigment 1 |
Some links on confounding and Simpson’s paradox:
January 21: Assignment 1 Presentations Video
Week 4
Feb 1st: Assignment 1 due by midnight.
February 2nd: Guest Lecture: Farah Bastien, Manager, Data Science/Data Engineer at MLSE (Maple Leaf Sports & Entertainment Partnership): Sports Analytics for the Leafs and the Raptors. Video
February 4th: Shapley values, causality, and Pearl’s do-calculus. Video
- SHAP values explained exactly how you wished someone explained to you
- A Unified Approach to Interpreting Model Predictions
- Making sense of Shapley values
- Causal Shapley Values
- Problems with Shapley-value-based explanations as feature importance measures
Week 5
February 9: Assignment 2 lab Video
February 11: Assignment 2 presentations Video
Week 6
Feb 17: Assignment 2 due by midnight.
Reading Week
Week 7
February 23: Guest Lecture: Wanying Zhao, Study design at Trilliam Foundation Video
February 25: Natural Language processing Video
- Latent Semantic Aalysis
- Topic Modeling + LDA Slides
- Original LDA Paper
- Illustrated Word2Vec
- RNN + Deep Language Model Slides
- Talk to Transformer
- To What Extent is GPT-3 Capable of Reasoning?
Week 8
March 2nd: Assignment 3 Lab Video
March 4th: Assignment 3 presentations Video
Week 9
March 9: Guest Lecture: Alp Kucukelbir, Chief Scientist, Fero Labs Video
March 10th: Assignment 3 due by midnight.
March 11: Lecture: Time Series Video
Week 10
March 16: Assignment 4 Lab Video
March 18: Assignment 4 presentations
Week 11
March 22: Assignment 4 due by midnight.
March 23: Guest Lecture: Robert Grant, Cancer Genomics Video
March 25: Surival analysis and clustering Video
Related reading:
- Related blog post
- DeepSurv paper
- Cox-nnet
- RNN-Surv
- Time-to-Event Prediction with Neural Networks and Cox Regression
Week 12
March 30: Lecture 11: Assignmnent 5 lab Video
April 1: Assignment 5 presentations
Week 13
April 6: Lecture 12: Stochastic Variational Inference for capturing uncertainty Video
April 8: Short paper presentations
April 12: Assignment 5 due by midnight.
Extra reading: