Schedule of Events
Lectures are held on Mondays, Tuesdays, and Thursdays.
On Mondays, lectures are 2:30 - 3:20pm in Chemistry 453.
On Tuesdays and Thursdays, lectures are 2:00 - 3:15pm in Geography/Geology 200C.
| Date | Topic | Links |
| Thurs, 8/15 | Lecture 1: Course Introduction | pptx | pdf |
| Mon, 8/19 | Workshop 0: Setting up your Python Environment | materials |
| Tues, 8/20 | Homework 1 Released | |
| Tues, 8/20 | Lecture 2: Python Crash Course | ipynb | html |
| Thurs, 8/23 | Lecture 3: Python Crash Course, Reloaded | ipynb | html |
| Mon, 8/26 | Workshop 1: Dask (Michael Hearn, Sasha Popov) | materials |
| Tues, 8/27 | Lecture 4: Linear algebra review | github | materials |
| Thurs, 8/29 | Lecture 5: Matrix decomposition review | github | materials |
| Mon, 9/2 | Labor Day! No classes | |
| Tues, 9/3 | Homework 1 Due | |
| Tues, 9/3 | Lecture 6: Dense Motion Analysis | pptx | pdf |
| Thurs, 9/5 | Lecture 7: Guest Lecturer Bahaa AlAila: Theory of Machine Learning | |
| Mon, 9/9 | Workshop 2: Spark and PySpark (Alireza Vaezi, Akram Farhadi, Elika Bozorgi) | pptx | materials |
| Tues, 9/10 | Homework 2 Released | |
| Tues, 9/10 | Lecture 8: Linear Dynamical Systems | pptx | pdf |
| Thurs, 9/12 | Lecture 9: Ethics in Data Science | pptx | pdf |
| Mon, 9/16 | Workshop 3: Tracking in OpenCV (Matthew Pooser, Alexander Kimbrell) | materials |
| Tues, 9/17 | Lecture 10: Guest Lecturer Prof. Elizabeth Davis | |
| Thurs, 9/19 | Lecture 11: Guest Lecturer Mojtaba Fazli | preprint |
| Mon, 9/23 | Workshop 4: DataFrames with Pandas (Will Moore, Tori Pirtle) | materials |
| Tues, 9/24 | Homework 2 Due ; Homework 3 Released | |
| Tues, 9/24 | Lecture 12: Graphs | pptx | pdf |
| Thurs, 9/26 | Lecture 13: Spectral Clustering | pptx | pdf |
| Mon, 9/30 | Workshop 5: Introduction to Keras (Aditya Patel, Zirak Khan) | materials |
| Tues, 10/1 | Lecture 14: Guest Lecturer Farid Gharehmohammadi: The application of evolutionary computation to advanced image processing | pptx | pdf |
| Thurs, 10/3 | Lecture 15: Semi-supervised learning on graphs | CANCELED |
| Mon, 10/7 | Midterm Review (no workshop) | |
| Tues, 10/8 | Homework 3 Due ; Homework 4 Released | |
| Tues, 10/8 | Lecture 16: Guest Lecturer Charles Morn | |
| Thurs, 10/10 | Midterm Exam | |
| Mon, 10/14 | Workshop 6: Bokeh interactive visualizations (Cheng Chen, Anh Tran) | materials |
| Tues, 10/15 | Lecture 17: Semi-supervised learning on graphs | pptx | pdf |
| Thurs, 10/17 | Lecture 18: Metric Learning | pptx | pdf |
| Mon, 10/21 | Workshop 7: JIT compilation with numba (Yulong Wang) | materials |
| Tues, 10/22 | Homework 4 Due | |
| Tues, 10/22 | Lecture 19: Kernel and Sparse PCA | pptx | pdf |
| Thurs, 10/24 | Lecture 20: Dictionary learning | pptx | pdf |
| Mon, 10/28 | Workshop 8: Bayesian ML with Edward (Hao Yang, Jialin Yang) | materials |
| Tues, 10/29 | Homework 5 Released | |
| Tues, 10/29 | Lecture 21: Kernel Methods | pptx | pdf |
| Thurs, 10/31 | Lecture 22: Neural networks | pptx | pdf |
| Mon, 11/4 | Workshop 9 | |
| Tues, 11/5 | Lecture 23: Backpropagation | pptx | pdf |
| Thurs, 11/7 | Lecture 24: Convolutional Neural Networks | pptx | pdf |
| Mon, 11/11 | Workshop 10: Natural Language Processing with NLTK (Elika Bozorgi, Ayda Farhadi) | materials gdoc |
| Tues, 11/12 | Homework 5 Due | |
| Tues, 11/12 | Lecture 25: Recurrent Neural Networks | pptx | pdf |
| Thurs, 11/14 | Lecture 26: Guest Lecturer Christian McDaniel: Graph Convolutional Networks | ipynb | pdf | html |
| Mon, 11/18 | Workshop 11: PyTorch (Michael Hearn, Sasha Popov) | gdoc |
| Tues, 11/19 | Lecture 27: Autoencoders | pptx | pdf |
| Thurs, 11/21 | Lecture 28: Deep Generative Models | pptx | pdf |
| Mon, 11/25 | Final Presentations |
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| Tues, 11/26 | \Final Presentations |
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| Mon, 12/2 | Final Presentations |
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| Tues, 12/3 | Final Presentations |
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| Fri, 12/6 | Final Project Deliverables Due |