Machine Learning at Brown University
Welcome to CSCI1420!
How can artificial systems learn from examples, and discover information buried in massive datasets? We explore the theory and practice of statistical machine learning, focusing on computational methods for supervised and unsupervised data analysis. Specific topics include empirical risk minimization, probably approximately correct learning, maximum likelihood parameter estimation, kernel methods, neural networks, the expectation maximization algorithm, and principal component analysis.
Time: 2:30 - 3:50pm, Tue & Thu
Location: Metcalf Research Building AUD
Announcement
Due to a large number of requests, we're asking anyone who is unable to register through C@B to join the waitlist.
Useful Links
Lectures
Time and Location: Tuesday & Thursday, 2:30pm to 3:50pm ET
Lecture Recordings: Lecture recordings are available through Canvas Media Library.
Schedule
| Date | Topics | Book Chapters | Notes |
|---|---|---|---|
| Thursday, Jan 23 | Intro, ERM framework | 1, 2.0, 2.1, 2.2 | Class notes Code |
| Tuesday, Jan 28 | Halfspaces and Perceptron | 9.0, 9.1.0, 9.1.2 | Class notes Code |
| Thursday, Jan 30 | Linear and Polynomial Regression | 9.2 | Class notes Code |
| Tuesday, Feb 4 | Logistic Regression | 9.3, 12.1.1, 14.0, 14.1.0 | Class notes Code |
| Thursday, Feb 6 | SGD, Data Prep, and other Practicalities | 14.3.0, 14.5.1 | Class notes Code |
| Tuesday, Feb 11 | PAC Learning | 2.3, 3 | Class notes Code |
| Thursday, Feb 13 | The Bias-Complexity Tradeoff | 5 | Class notes Code |
| Tuesday, Feb 18 | LONG WEEKEND, NO CLASS | Class notes Code | |
| Thursday, Feb 20 | Model Selection, Validation, and Regularization | 11.0, 11.2, 11.3, 13.1, 13.4 | Class notes Code |
| Tuesday, Feb 25 | Boosting | 10 | Class notes Code |
| Thursday, Feb 27 | Decision Trees | 18 | Class notes Code |
| Tuesday, Mar 4 | Learning via Uniform Convergence | 4 | Class notes Code |
| Thursday, Mar 6 | VC Dimension | 6, 9.1.3 | Class notes Code |
| Tuesday, Mar 11 | Naive Bayes | 24.0, 24.1, 24.2 | Class notes Code |
| Thursday, Mar 13 | K-Nearest Neighbors / Fairness in Machine Learning | 19 | Class notes Code |
| Tuesday, Mar 18 | Support Vector Machines | 15 | Class notes Code |
| Thursday, Mar 20 | Kernel Methods | 16 | Class notes Code |
| Tuesday, Mar 25 | NO CLASS (SPRING BREAK) | Class notes Code | |
| Thursday, Mar 27 | NO CLASS (SPRING BREAK) | Class notes Code | |
| Tuesday, Apr 1 | Neural Networks | 20.0, 20.1, 20.2, 20.3 | Class notes Code |
| Thursday, Apr 3 | Backpropagation | 20.6 | Class notes Code |
| Tuesday, Apr 8 | Deep Learning | Class notes Code | |
| Thursday, Apr 10 | K-Means | 22.0, 22.2, 22.5 | Class notes Code |
| Tuesday, Apr 15 | Expectation Maximization | 24.4 | Class notes Code |
| Thursday, Apr 17 | Principal Component Analysis | 23.0, 23.1 | Class notes Code |
| Tuesday, Apr 22 | Ethics in Machine Learning | Class notes Code | |
| Thursday, Apr 24 | Cutting Edge Machine Learning | Class notes Code |
Homework Policy
All assignments are due at 12:00pm noon. Written and programming assignments are to be submitted to Gradescope. See the missive for more information on late days and extensions.
Assignments
The report template can be found here.
| Description | Release | Due | Latex | Code | Solutions |
|---|---|---|---|---|---|
| #1. Review, Python | Jan 23 | Jan 30 | Latex | Code | Solutions |
| #2. Halfspaces, Linear and Polynomial Regression | Jan 30 | Feb 6 | Latex | Code | Solutions |
| #3. Logistic Regression | Feb 6 | Feb 13 | Latex | Code | Solutions |
| #4. PAC Learning and the Bias-Complexity Tradeoff | Feb 13 | Feb 20 | Latex | Code | Solutions |
| #5. Model Selection, Validation, and Regularization | Feb 20 | Feb 27 | Latex | Code | Solutions |
| #6. Boosting and Decision Trees | Feb 27 | Mar 6 | Latex | Code | Solutions |
| #7. Uniform Convergence and VC Dimension | Mar 6 | Mar 13 | Latex | Code | Solutions |
| #8. Naive Bayes and Fairness | Mar 13 | Mar 20 | Latex | Code | Solutions |
| #9. SVM and Kernels | Mar 20 | Apr 3 | Latex | Code | Solutions |
| #10. Neural Networks | Apr 3 | Apr 10 | Latex | Code | Solutions |
| #11. Deep Learning | Apr 10 | Apr 17 | Latex | Code | Solutions |
| #12. Clustering | Apr 17 | Apr 24 | Latex | Code | Solutions |
| #13. Dimensionality Reduction | Apr 24 | May 1 | Latex | Code | Solutions |
| Final Exam | May 14, 12pm | May 15, 11:59pm | Latex | Code | Solutions |
Calendar
Refer to the calendar below for the most up-to-date lecture and office hour schedule.
Meet Our Staff
Stephen Bach
he/him | Professor
🏠 Providence, RI | 🍦 Red Velvet Cake
Assistant professor with an awesome team of students. Check out our research group! (link under 'Useful Links')
Andrew Yang
he/him | HTA
🏠 Cincinnati, OH | 🍦 tiramisu
I'm a senior studying APMA-CS and Biology. I'm passionate about AI/ML applied to biosciences/medicine!
Jania Vandevoorde
she/her | HTA
🏠 Dubai, UAE | 🍦 Strawberry Cheesecake
Welcome to ML! I'm a senior studying Computer Science and Statistics. I love running, traveling, and reading. This is my 5th and last time HTAing so let's make it a great semester!
Prithvi Oak
he/him | HTA
🏠 New Delhi, India | 🍦 Pizookie
Hey folks! I'm a senior studying Applied Math-CS. In my free time, you'll catch me jamming in Steinert, watching F1, or sipping matcha. It is a treat to be your HTA!
Alex Liang
he/him | UTA
🏠 Shanghai | 🍦 Tiramisu
Hi, my name is Alex and I'm a senior studying CS and APMA. In my free time, I love to play basketball and cook.
Alex Lin
he/him | UTA
🏠 Boston, MA | 🍦 Chinese Pumpkin Cake
It's my last semester! I like training and watching MMA, working out, and cooking.
Hrithik Nambiar
he/him | UTA
🏠 Kochi, India | 🍦 Ras malai
Hey there! I enjoy computer science and math. I love to read books, play soccer, and run. Excited to meet y'all :)
Jaideep Naik
he/him | UTA
🏠 South Windsor, CT | 🍦 Kaju Katli
Hey everyone, I'm a junior studying APMA + CS. I love playing soccer, hiking, and working out. Excited to be TA-ing again for 1420!
Jean Yoo
she/her | UTA
🏠 Salt Lake City, UT | 🍦 Cinnamon rolls
I'm a senior studying CS and APMA. I love to run, play guitar, and solve NYT word games.
Kyle Lee
he/him/his | UTA
🏠 Santa Clara, California | 🍦 Ice Cream
Hi — I'm a CS concentrator with a particular interest in AI/ML. During my free time, I enjoy basketball, skiing, hiking, and whitewater rafting.
Letian Yu
she/her | UTA
🏠 Changzhou, Jiangsu Province, China | 🍦 fruit tart! 🍇
Hi, I am a 2nd-year master's student studying data science. I do photograph and enjoy jazz hip-hop. :)
Peter Popescu
he/him | UTA
🏠 Columbia, Missouri | 🍦 Mochi ice cream
Heya! I'm Peter, a junior studying cs and apma. I love climbing, playing games with friends, and messing with my mac's dotfiles. Ask me anything about stationery or jazz fusion!
Seehanah Tang
she/her | UTA
🏠 Holmdel, NJ | 🍦 mango sticky rice
Hi, I'm a senior studying APMA-CS. My favorite things are shengji, (sour) dried mangos, and hiking!
Siddharta Laloux
he/him | UTA
🏠 Paris | 🍦 Éclair, crême brulée, jaleebi, falooda
Hello! I am a third-year Sc.B. candidate in APMA-CS and Sanskrit Classics. Outside of my academic interests in machine learning, probability and language, I enjoy chocolate, most caffeinated drinks, and desserts of all sorts.
Thomas Chang
he/him | UTA
🏠 Pittsburgh, PA | 🍦 Cheesecake
Hi! I'm a senior studying applied math and computer science. When I'm not in the Sci Li, I love reading or playing the viola. Looking forward to a great semester with everyone!