Schedule of Events

Class meetings are held on Mondays, Tuesdays, and Thursdays.

On Mondays, workshops are 3:00 - 3:50pm in Forest Resources-4 0517.

On Tuesdays and Thursdays, lectures are 2:20 - 3:35pm in Physics 0303.

Date Topic Links
Thurs, 8/19 Lecture 1: Course Introduction pptx | pdf | mp4
Mon, 8/23 Workshop 0: Setting up your Python Environment materials | mp4
Tues, 8/24 Homework 1 Released pdf | handout
Tues, 8/24 Lecture 2: Python Crash Course, Part 1 html | ipynb | mp4
Thurs, 8/26 Lecture 3: Python Crash Course, Part 2 html | ipynb | mp4
Mon, 8/30 Workshop 1 (Nikhil Ranjan): Pandas & Dask zip | mp4
Tues, 8/31 Lecture 4: Linear Algebra Review github | pt1, pt2, pt3
Thurs, 9/2 Lecture 5: Linear Algebra Review github | pt1, pt2
Mon, 9/6 Labor Day! No classes
Tues, 9/7 Lecture Cancelled for Rosh Hashanah
Thurs, 9/9 Lecture 6: Dense Motion Analysis pptx | pdf | mp4
Mon, 9/13 Workshop 2 (Harrison Ham, Sean Kan, Nikhil Ranjan): Gradient Boosted Trees with xgboost materials
Tues, 9/14 Homework 1 Due
Tues, 9/14 Lecture 7: Linear Dynamical Systems pptx | pdf | mp4
Thurs, 9/16 Lecture Cancelled for Yom Kippur
Mon, 9/20 Workshop 3 (Winston Weinmann and Nicholas Findley): scikit-learn materials | mp4
Mon, 9/20 Homework 2 Released pdf | handout
Tues, 9/21 Lecture 8: Linear and Ensemble Methods pptx | pdf | mp4
Thurs, 9/23 Lecture 9: Ethics in Data Science pptx | pdf | mp4
Mon, 9/27 Workshop 4 (Steven Zhang, Chenqian Xu, Xin He): Tensorflow materials | mp4
Tues, 9/28 Lecture 10: Guest Lecturer Farid Gharehmohammadi, Ph.D. Candidate: Evolutionary Computation in Computer Vision pptx | pdf | mp4
Thurs, 9/30 Lecture 11: Guest Lecturer Dr. Roi Ceren: Reinforcement Learning in Theory and Practice pptx | pdf | mp4
Mon, 10/4 Workshop 5 (Nick Findley, Whit Weinmann, Gabrielle Panlaqui): SQL, MySQL, and SQLite materials | mp4
Tues, 10/5 Homework 3 Released pdf | handout
Tues, 10/5 Lecture 12: Graphs pptx | pdf | mp4
Thurs, 10/7 Homework 2 Due
Thurs, 10/7 Lecture 13: Spectral Clustering pptx | pdf | mp4
Mon, 10/11 Midterm Review (no workshop) pptx | pdf
Tues, 10/12 Midterm Exam
Thurs, 10/14 Lecture 14: Semi-supervised Learning pptx | pdf | mp4
Thurs, 10/14 Final Project Proposals Due
Mon, 10/18 Workshop 6 (Albert You, Jackson Cown): NLTK materials | mp4
Tues, 10/19 Lecture 15: Embeddings I (Metric Learning) pptx | pdf | mp4
Thurs, 10/21 Lecture 16: Embeddings II (Kernel & Sparse PCA, Dictionary Learning) pptx | pdf | mp4
Thurs, 10/21 Homework 3 Due
Mon, 10/25 Workshop 7 (Ociel Marin, Parker Ciaramella): JAX materials | mp4
Tues, 10/26 Homework 4 Released pdf | handout
Tues, 10/26 Lecture 17: Kernel Methods and SVMs pptx | pdf | mp4
Thurs, 10/28 Lecture 18: Neural Networks pptx | pdf | mp4
Thurs, 10/28 Final Project: Update 1 Due
Mon, 11/1 Workshop 8 (Gabrielle Panlaqui, Ben Taylor, Albert You): OpenCV materials | mp4
Tues, 11/2 Lecture 19: Backpropagation pptx | pdf | mp4
Thurs, 11/4 Lecture 20: Convolutional Neural Networks pptx | pdf | mp4
Mon, 11/8 Workshop 9 (Xin He, Yi Zhou, Chenqian Xu): Plotly materials | mp4
Tues, 11/9 Lecture 21: Deep Autoencoders pptx | pdf | mp4
Thurs, 11/11 Lecture 22: Guest Lecturer Marcus Hill, Ph.D. Candidate on Graph Convolutional Networks
Thurs, 11/11 Homework 4 Due
Mon, 11/15 Workshop 10 (Trisha Nayak, Alireza Vaezi, Vijay Iyengar): Julia materials | mp4
Tues, 11/16 Homework 5 Released pdf | handout
Tues, 11/16 Lecture 23: Recurrent Neural Networks pptx | pdf | mp4
Thurs, 11/18 Lecture 24: Guest Lecturer Meekail Zain, Ph.D. Student on Deep Representation Learning
Thurs, 11/18 Final Project: Update 2 Due
Mon, 11/22 Workshop 11 (Sean Kan, Harrison Ham, Vijay Iyengar): yfinance materials | mp4
Tues, 11/23 Lecture 25: Deep Generative Models pptx | pdf | mp4
Thurs, 11/21 Thanksgiving Break! No classes
Mon, 11/29 Workshop 12 (Devin Hajjari, Alireza Vaezi, Ben Taylor): PyTorch Lightning materials | mp4
Tues, 11/30 Final Project Talks
Thurs, 12/2 Final Project Talks
Thurs, 12/2 Homework 5 Due
Mon, 12/6 Final Project Talks