Introduction to Machine Learning
-
Instructor: Yao-Liang Yu
-
Email: yaoliang.yu@uwaterloo.ca
-
Time and location:
- TTh 08:30-09:50, DWE 3522
- TTh 10:00-11:20, DWE 1501
- TTh 13:00-14:20, E2 1732
-
Office hour: TTh 14:30-15:30 at DC3617 or by email appointment
-
TAs:
- Ganjidoost, Ehsan (eganjido)
- Hu, Theo (z97hu)
- Lu, Haoye (h229lu)
- Lu, Yiwei (y485lu) x 2
- Mouzakis, Argyris (amouzaki)
Lectures (Tentative)
| Date | Topic | Slides | Notes | |
| Jan 07, 2025 | Introduction | opt, stat | ||
| Jan 09, 2025 | Perceptron | |||
| Jan 14, 2025 | Linear Regression | |||
| Jan 16, 2025 | Logistic Regression | |||
| 04 | Jan 21, 2025 | Hard-margin SVM | ||
| 05 | Jan 23, 2025 | Soft-margin SVM | ||
| 06 | Jan 28, 2025 | Reproducing Kernels | ||
| 07 | Jan 30, 2025 | Fully Connected NNs | ||
| 08 | Feb 04, 2025 | Convolutional NNs | ||
| 09 | Feb 06, 2025 | Graph NNs | ||
| 10 | Feb 11, 2025 | |||
| 11 | Feb 13, 2025 | Decision Trees | ||
| reading week | ||||
| reading week | ||||
| 12 | Feb 25, 2025 | Boosting | ||
| 13 | Feb 27, 2025 | GANs | ||
| 14 | Mar 04, 2025 | Flows | ||
| 15 | Mar 06, 2025 | Attention | ||
| 16 | Mar 11, 2025 | VAEs | ||
| 17 | Mar 13, 2025 | Optimal Transport | ||
| 18 | Mar 18, 2025 | Diffusion | ||
| 19 | Mar 20, 2025 | Contrastive Learning | ||
| 20 | Mar 25, 2025 | Robustness | ||
| 21 | Mar 27, 2025 | Fairness | ||
| 22 | Apr 01, 2025 | Privacy | ||
| 23 | Apr 03, 2025 | Valuation | ||
Assignment (Tentative)
-
spambase X and spambase y
-
If you extract spambase from the UCI repository yourself, you’ll notice that on the first pass perceptron only makes 2 mistakes! This is because by default all positive examples happen to come before all negative examples in spambase. In the provided files above, we have randomly permuted the positives and negatives. A good practice is to randomly permute the training set in each pass. You could optionally do this in your implementation.
-
activity names, 10299 instances, 561 features, 6 labels
Project
TBD
Textbook
There is no required textbook, but the following fine texts are recommended.
- Francis Bach. Learning Theory from First Principles. MIT Press, 2024.
- Tong Zhang. Mathematical Analysis of Machine Learning Algorithms. Cambridge University Press, 2023.
- Moritz Hardt and Benjamin Recht. Patterns, Predictions, and Actions. Princeton University Press, 2022.
- Kevin Patrick Murphy. Probabilistic Machine Learning: Advanced Topics. MIT Press, 2023.
- Kevin Patrick Murphy. Probabilistic Machine Learning: An Introduction. MIT Press, 2022.
- Aston Zhang, Zack C. Lipton, Mu Li and Alex J. Smola. Dive into Deep Learning. Cambridge University Press, 2023.
- Ian Goodfellow, Yoshua Bengio and Aaron Courville. Deep Learning. MIT Press, 2016.
- Thomas Mack. The Math You Need: A Comprehensive Survey of Undergraduate Mathematics. MIT Press, 2023.
- Thomas A. Garrity. All the Math You Missed (But Need to Know for Graduate School). 2nd Edition. Cambridge University Press, 2021.
- Gilbert Strang. Linear Algebra and Learning from Data. SIAM, 2019.
- Stephen Boyd and Lieven Vandenberghe. Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares. Cambridge University Press, 2018.
Resource
- Colab
- Canada Compute, require a faculty (e.g., supervisor) sponsor
Policy
Academic Integrity: In order to maintain a culture of academic integrity, members of the University of Waterloo community are expected to promote honesty, trust, fairness, respect and responsibility. Check the university website for more information.
Grievance: A student who believes that a decision affecting some aspect of his/her university life has been unfair or unreasonable may have grounds for initiating a grievance. Read Policy 70, Student Petitions and Grievances, Section 4. When in doubt please be certain to contact the department’s administrative assistant who will provide further assistance.
Discipline: A student is expected to know what constitutes academic integrity to avoid committing an academic offence, and to take responsibility for his/her actions. A student who is unsure whether an action constitutes an offence, or who needs help in learning how to avoid offences (e.g., plagiarism, cheating) or about “rules” for group work/collaboration should seek guidance from the course instructor, academic advisor, or the undergraduate Associate Dean. For information on categories of offences and types of penalties, students should refer to Policy 71, Student Discipline. For typical penalties check Guidelines for the Assessment of Penalties.
Appeals: A decision made or penalty imposed under Policy 70 (Student Petitions and Grievances) (other than a petition) or Policy 71 (Student Discipline) may be appealed if there is a ground. A student who believes he/she has a ground for an appeal should refer to Policy 72 (Student Appeals).
Note for Students with Disabilities: The Office for Persons with Disabilities (OPD), located in Needles Hall, Room 1132, collaborates with all academic departments to arrange appropriate accommodations for students with disabilities without compromising the academic integrity of the curriculum. If you require academic accommodations to lessen the impact of your disability, please register with the OPD at the beginning of each academic term.
Mental Health: If you or anyone you know experiences any academic stress, difficult life events, or feelings like anxiety or depression, we strongly encourage you to seek support.
On-campus Resources
- Campus Wellness https://uwaterloo.ca/campus-wellness/
- Counselling Services: counselling.services@uwaterloo.ca / 519-888-4567 ext 32655 / Needles Hall North 2nd floor, (NH 2401)
- MATES: one-to-one peer support program offered by Federation of Students (FEDS) and Counselling Services: mates@uwaterloo.ca
- Health Services service: located across the creek from Student Life Centre, 519-888-4096.
Off-campus Resources
- Good2Talk (24/7): Free confidential help line for post-secondary students. Phone: 1-866-925-5454
- Here 24/7: Mental Health and Crisis Service Team. Phone: 1-844-437-3247
- OK2BME: set of support services for lesbian, gay, bisexual, transgender or questioning teens in Waterloo. Phone: 519-884-0000 extension 213
Diversity: It is our intent that students from all diverse backgrounds and perspectives be well served by this course, and that students’ learning needs be addressed both in and out of class. We recognize the immense value of the diversity in identities, perspectives, and contributions that students bring, and the benefit it has on our educational environment. Your suggestions are encouraged and appreciated. Please let us know ways to improve the effectiveness of the course for you personally or for other students or student groups. In particular:
- We will gladly honour your request to address you by an alternate/preferred name or gender pronoun. Please advise us of this preference early in the semester so we may make appropriate changes to our records.
- We will honour your religious holidays and celebrations. Please inform of us these at the start of the course.
- We will follow AccessAbility Services guidelines and protocols on how to best support students with different learning needs.