Welcome to the Canvas Site for DD2424, 2022
Important announcement.
The lectures for this course will happen in-person on campus according to the Schedule unless notified otherwise (change in the status of the pandemic, teacher has some COVID like symptoms etc.). If the lecture is given in-person, it will not be recorded, but the slides will be made available on-line and you always have the option to look at the videos from last year where much of the material overlaps with this year's version of the course.
Course Goals
The course begins on March 22, 2022. We are looking forward to introducing you to the exciting field of deep learning and also teaching you the nitty gritty details so that at the end of the course you will
- feel confident implementing and training networks from scratch,
- have the ability to read many research papers in the area and understand what they are talking about,
- have gained experience using the most popular deep learning software packages.
If viewing Canvas page before March 22
The Canvas webpage is still a work in progress. Please check again the week the course starts if there is information you are looking for but have not found it yet.
Material and Information available on this Canvas Webpage
Provided Learning Material
- Lecture Schedule & Material - contains the schedule and the slides to all the lectures given in the course.
- Online educational resources about deep learning - contains links to online resources providing auxiliary and complementary learning resources to the lecture slides and assignments.
GPU Resources & Information
- Information about available GPU resources - information about the GPU resources available to the course.
- Information about Deep Learning software packages
Scheduling Information
- Schedule for Help Sessions - contains the date and location of the Help Sessions.
Assignments & Project Information
- Assignment 1
- Assignment 2
- Assignment 3
- Assignment 4
- Project Information
- Virtual Poster Session (May 27)
- Re-exam Virtual Poster Session
- Project Information for PhD students
General Information
- Profile of TAs - has a brief bio and expertise guide for each TA
- FAQ - contains answers to the most common high-level admin questions we get.