Foundations of Deep Learning
Prof. Dr. Frank Hutter, Prof. Dr. Abhinav Valada, Prof. Dr. Joschka Bödecker
Co-Organizers:
Steven Adriaensen Tim Frederic Runge
Deep learning is one of the fastest growing and most exciting fields. This course will provide you with a clear understanding of the fundamentals of deep learning including the foundations to neural network architectures and learning techniques, and everything in between.
| Time: | Wednesday, 14.15-15.45 First meeting on November 4th 2020. |
| Location: | This course will be fully virtual. |
| Learning Platform: | ILIAS |
Course Overview
The course will be taught in english and will follow a flipped classroom approach.
Every week there will be:
- a video lecture
- an exercise sheet
- a flipped classroom session (virtual/online, Wednesdays 14:15-15:45)
At the end, there will be a written exam (likely on-site).
Exercises must be completed in groups and must be submitted a week (+ 1 day) after their release. Your submissions will be graded and you will receive weekly feedback. Your final grade will be solely based on a written examination, however a passing grade for the exercises is a prerequisite for passing the course.
Online course: All material will be made available online and course participation will not require in-person presence.
On-site exam: The exam will take place on campus and require you to be present in person.
Course Schedule
The following are the dates for the release of video lectures:
04.11.20 - Week 1: Overview of Deep Learning
11.11.20 - Week 2: From Logistic Regression to MLPs
18.11.20 - Week 3: Backpropagation
25.11.20 - Week 4: Optimization
02.12.20 - Week 5: Regularization
09.12.20 - Week 6: Convolutional Neural Networks (CNNs)
16.12.20 - Week 7: Recurrent Neural Networks (RNNs)
06.01.21 - Week 8: Practical Methodology & Architectures
13.01.21 - Week 9: Hyperparameter Optimization
20.01.21 - Week 10: Neural Architecture Search
27.01.21 - Week 11: Auto-Encoders, Variational Auto-Encoders, GANs
03.02.21 - Week 12: Uncertainty in Deep Learning
On the same day, there is a flipped classroom session about the material released the week before. We will be using Zoom and the meeting link will be made available on ILIAS the same day.
In the first session (on 04.11.20) you will instead get additional information about the course and get the opportunity to ask general questions (and form groups!)
While there is no need to prepare for this first session, we encourage you to already think about forming teams.
The first exercise on 'Week 1: Overview of Deep Learning' is due on 12.11.20 at 23:59.
The last flipped classroom session is held on 10.02.21.
Questions?
If you have a question, please post it in the ILIAS forum (so everyone can benefit from the answer).
Alternatively, you can also email dl-orga-ws20@cs.uni-freiburg.de