GSERM 2023 Deep Learning: Fundamentals and Applications 🏔️
Grüezi! 🖐️ Welcome to our GSERM course Deep Learning: Fundamentals and Applications, taught by Prof. Dr. Damian Borth and Prof. Dr. Korbinian 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 taught by Marco Schreyer. The lab materials for Python programming, Machine Learning, and Deep Learning are available in and accessible through this GitHub repository.
Please use a laptop computer (not a tablet) for the lab courses to fully participate.
Viel Spass beim Programmieren! 🎉 (Happy Coding!)
Course Logistics 🗓️
- Lectures: Daily 09:15-12:30 CEST ⏰ , Zoom links are posted on Canvas.
- Labs: Daily 13:30-15:15 CEST, 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 CEST, please send us a corresponding invitation via mail.
- Announcements: All course-related announcements and questions will happen on Canvas.
Course Code Lab Notebooks 
Just like the timetable of the Swiss Federal Railways 🚞, the following table lists all lab sessions including the launchers of the corresponding notebooks 📚 . In order to start the notebooks in the respective cloud environment, click on the corresponding launchers. We aim to upload each lab notebook the day before the lab respectively.
| Date | Lab | Topic | Description | Binder Notebook | Gesis Notebook | Colab Notebook |
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| < Mon, June 5th | Lab 00 | Prerequisite | Test Notebook |  |
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| < Mon, June 5th | Lab 01 | Prerequisite | Python Basics | |
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| < Mon, June 5th | Lab 02 | Prerequisite | Python Libraries | |
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| Mon, June 5th | Lab 03 | Machine Learning | (Naive) Bayes Theorem | |
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| Mon, June 5th | Bonus 1 | Machine Learning | Support Vector Machines (SVMs) | |
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| Tue, June 6th | Lab 04 | Deep Learning | Artificial Neural Networks (ANNs) | |
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| Wed, June 7th | Lab 05 | Deep Learning | Convolutional Neural Networks (CNNs) | |
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| Wed, June 7th | Bonus 2 | Deep Learning | Residual Neural Networks (ResNets) | |
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| Wed, June 7th | Lab 06 | Deep Learning | Autoencoder Neural Networks (AENs) | |
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| Thu, June 8th | Lab 07 | Deep Learning | Recurrent Neural Networks (RNNs) | |
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| Thu, June 8th | Bonus 3 | Deep Learning | Recurrent Neural Networks (RNNs) | |
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| Fri, June 9th | Lab 08 | Deep Learning | Attention Neural Networks | |
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| < Sun, July xxth | - | Deep Learning | Assignment | tba | tba | tba |
You can also board the train to the labs by launching all lab notebooks in either
Questions?
Please don't hesitate to send us all your questions using the course mail address:
