Welcome to our GSERM course Deep Learning: Fundamentals and Applications, taught by Prof. Dr. Damian Borth and Prof. Dr. Korbinan Riedhammer. In this course, theoretical sessions and practical hands-on coding lab sessions alternate to provide a better learning experience.
The guided coding labs will be (partially) thaught by Marco Schreyer. The lab materials for Python programming, Machine Learning und Deep Learning are available in and accessible through this repository.
Please use a laptop computer for the lab courses (not a tablet) to be able to fully participate in the labs.
Happy Coding!
- Lectures: Daily 09:15-12:30 CET, Zoom links are posted on Canvas.
- Labs: Daily 13:30-15:15 CET, Zoom links are posted on Canvas.
- Zoom Videos: Will be posted on Canvas shortly after each lecture/lab.
- Office Hours: Daily 16:00-17:00 CET, please send us a corresponding invitation via mail.
- Announcements: All course-related announcements and questions will happen on Canvas.
The following table lists all lab session and coding challenge session incl. the launchers of the corresponding notebooks. In order to start the notebooks in the respective cloud environment just click on the to corresponding launchers. We aim to upload each lab notebook the day before the lab respectively.
| Date | Lab | Topic | Description | Binder Notebook | Colab Notebook |
|---|---|---|---|---|---|
| < Mon, June 20th | Lab 00 | Prerequisite | Test Notebook |  |
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| < Mon, June 20th | Lab 01 | Prerequisite | Python Basics | |
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| < Mon, June 20th | Lab 02 | Prerequisite | Python Libraries | |
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| Mon, June 20th | Lab 03 | Machine Learning | (Naive) Bayes Theorem | |
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| Mon, June 20th | Bonus 1 | Machine Learning | Support Vector Machines (SVMs) | |
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| Tue, June 21st | Lab 04 | Deep Learning | Artificial Neural Networks (ANNs) | |
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| Wed, June 22nd | Lab 05 | Deep Learning | Convolutional Neural Networks (CNNs) | |
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| Wed, June 22nd | Bonus 2 | Deep Learning | Residual Neural Networks (ResNets) | |
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| Wed, June 22nd | Lab 06 | Deep Learning | Autoencoder Neural Networks (AENs) | |
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| Thu, June 23rd | Lab 07 | Deep Learning | Recurrent Neural Networks (RNNs) | |
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| Thu, June 23rd | Bonus 3 | Deep Learning | Recurrent Neural Networks (RNNs) | |
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| Fri, June 24th | Lab 08 | Deep Learning | Attention Neural Networks | |
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| < Sun, July 17th | - | Deep Learning | Assignment | |
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Launch all lab notebooks in either
Pls. don't hesitate to send us all your questions using the course mail address:
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