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

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.

DD2424/FDD3424 deep22 VT22-1 Deep Learning in Data Science