This is the course homepage for CPSC 330: Applied Machine Learning at the University of British Columbia. You are looking at the current version (Sep-Dec 2023).
- Andrew Roth (Section 101: Tue Thu 15:30 to 17:00 Swing Space 121)
- Varada Kolhatkar (Section 102: Tue Thu 11:00 to 12:30 West Mall Swing Space 221)
- Michelle Pang ([email protected])
- Chen Liu ([email protected])
- Colleen Rideout ([email protected])
- Justice Sefas ([email protected])
- Mahsa Zarei ([email protected])
- Miranda Chan ([email protected])
- Sparsh Trivedy ([email protected])
- Vee Rajesh Bahel ([email protected])
- Wilson Tu ([email protected])
- Yeojun Han ([email protected])
© 2023 Varada Kolhatkar and Mike Gelbart
Software licensed under the MIT License, non-software content licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License. See the license file for more information.
- Calendar
- Course GitHub page
- Course Jupyter book
- Canvas: You will find the class recordings via Panopto in Canvas
- Piazza
- iClicker Cloud
- Gradescope
- Course videos YouTube channel
- Syllabus / administrative info
- Other course documents
Usually the homework assignments will be due on Mondays (except next week) and will be released on Tuesdays. We'll also add the due dates in the Calendar. If you find inconsistencies in due dates, follow the due date in the Calendar. For this course, we'll assume that the Calendar is always right!
| Assessment | Due date | Where to find? | Where to submit? |
|---|---|---|---|
| hw1 | Sept 12, 11:59 pm | Github repo | Gradescope |
| Syllabus quiz | Sept 19, 11:59 pm | Canvas | Canvas |
| hw2 | Sept 18, 11:59 pm | Github repo | Gradescope |
| hw3 | Oct 02, 11:59 pm | Github repo | Gradescope |
| hw4 | Oct 10, 11:59 pm | Github repo | Gradescope |
| Midterm | Oct 26 6:00 pm to 7:20 pm | Canvas | Canvas |
| hw5 | Oct 30, 11:59 pm | Github repo | Gradescope |
| hw6 | November 13, 11:59 pm | Github repo | Gradescope |
| hw7 | November 20, 11:59 pm | Github repo | Gradescope |
| hw8 | November 27, 11:59 pm | Github repo | Gradescope |
| hw9 | December 7, 11:59 pm | Github repo | Gradescope |
| Final exam | TBA | Canvas | Canvas |
Live lectures: The lectures will be in-person. The location can be found in the Calendar. The lectures will be recorded and will be made available after 5 pm on lecture days. You can find the link of Panopto videos in Canvas. That said, consider the recordings a backup resource and do not completely rely on it. You will get a lot more out of the course if you show up in person.
This course will be run in a semi flipped classroom format. There will be pre-watch videos for many lectures, at least in the first half of the course. All the videos are available on YouTube and are posted in the schedule below. Try to watch the assigned videos before the corresponding lecture. During the lecture, we'll summarize the important points from the videos and focus on demos, iClickers, worksheets, and Q&A.
We'll be developing lecture notes directly in this repository. So if you check them before the lecture, they might be in a draft form. Once they are finalized, they will be posted in the Course Jupyter book.
| Date | Topic | Assigned videos | vs. CPSC 340 |
|---|---|---|---|
| Sep 5 | UBC Imagine Day - no class | ||
| Sep 7 | Course intro | 📹 Pre-watch: 1.0 | n/a |
| Sep 12 | Decision trees | 📹 Pre-watch: 2.1, 2.2, 2.3, 2.4 | less depth |
| Sep 14 | ML fundamentals | 📹 Pre-watch: 3.1, 3.2, 3.3, 3.4 | similar |
| Sep 19 |
|
📹 Pre-watch: 4.1, 4.2, 4.3, 4.4 | less depth |
| Sep 21 | Preprocessing, sklearn pipelines |
📹 Pre-watch: 5.1, 5.2, 5.3, 5.4 | more depth |
| Sep 26 | More preprocessing, sklearn ColumnTransformer, text features |
📹 Pre-watch: 6.1, 6.2 | more depth |
| Sep 28 | Linear models | 📹 Pre-watch: 7.1, 7.2, 7.3 | less depth |
| Oct 03 | Hyperparameter optimization, overfitting the validation set | 📹 Pre-watch: 8.1, 8.2 | different |
| Oct 05 | Evaluation metrics for classification | 📹 Reference: 9.2, 9.3,9.4 | more depth |
| Oct 10 | No class. Monday classes moved to Tuesday. | ||
| Oct 12 | Regression metrics | 📹 Pre-watch: 10.1 | more depth on metrics less depth on regression |
| Oct 17 | Ensembles | 📹 Pre-watch: 11.1, 11.2 | similar |
| Oct 19 | Feature importances, model interpretation | 📹 Pre-watch: 12.1,12.2 | feature importances is new, feature engineering is new |
| Oct 24 | Feature engineering and feature selection | None | less depth |
| Oct 26 | Midterm. No classes. | ||
| Oct 31 | Clustering | 📹 Pre-watch: 14.1, 14.2, 14.3 | less depth |
| Nov 02 | More clustering | 📹 Pre-watch: 15.1, 15.2, 15.3 | less depth |
| Nov 07 | Simple recommender systems | less depth | |
| Nov 14 | Midterm break - no class | ||
| Nov 16 | Text data, embeddings, topic modeling | 📹 Pre-watch: 16.1, 16.2 | new |
| Nov 21 | Neural networks and computer vision | less depth | |
| Nov 23 | Time series data | (Optional) Humour: The Problem with Time & Timezones | new |
| Nov 28 | Survival analysis | 📹 (Optional but highly recommended)Calling Bullshit 4.1: Right Censoring | new |
| Nov 30 | Ethics | 📹 (Optional but highly recommended) |
new |
| Dec 05 | Communication | 📹 (Optional but highly recommended) |
new |
| Dec 07 | Model deployment and conclusion | new |
Please read Covid Campus Rules.
Masks: This class is going to be in person. UBC no longer requires students, faculty and staff to wear non-medical masks, but continues to recommend that masks be worn in indoor public spaces.
Your personal health: If you are ill or believe you have COVID-19 symptoms or been exposed to SARS-CoV-2 use the Thrive Health self-assessment tool for guidance, or download the BC COVID-19 Support App for iOS or Android device and follow the instructions provided. Follow the advice from Public Health.
Stay home if you have recently tested positive for COVID-19 or are required to quarantine. You can check this website to find out if you should self-isolate or self-monitor.
Your precautions will help reduce risk and keep everyone safer. In this class, the marking scheme is intended to provide flexibility so that you can prioritize your health and still be able to succeed:
- All course notes will be provided online.
- All homework assignments can be done and handed in online.
- All exams will be held online. (But you need to be present in the classroom to write the exam unless there is a legitimate reason for not doing so.)
- Most of the class activity will be video recorded and will be made available to you.
- There will be at least a few office hours which will be held online.
UBC’s Point Grey Campus is located on the traditional, ancestral, and unceded territory of the xwməθkwəy̓əm (Musqueam) peple. The land it is situated on has always been a place of learning for the Musqueam people, who for millennia have passed on their culture, history, and traditions from one generation to the next on this site.
It is important that this recognition of Musqueam territory and our relationship with the Musqueam people does not appear as just a formality. Take a moment to appreciate the meaning behind the words we use:
TRADITIONAL recognizes lands traditionally used and/or occupied by the Musqueam people or other First Nations in other parts of the country.
ANCESTRAL recognizes land that is handed down from generation to generation.
UNCEDED refers to land that was not turned over to the Crown (government) by a treaty or other agreement.
As you begin your journey at UBC, take some time to learn about the history of this land and to honour its original inhabitants.