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This course will be offered by 3D AI Lab in SS25. Please visit this website for more information.
Introduction to Deep Learning (IN2346)
Welcome to the Introduction to Deep Learning course offered in WS24/25.
Course Structure
| What | When | Where | Who |
|---|---|---|---|
| Lecture | Tuesdays, 14:00-16:00 | MI HS 1 | Prof. Dr. Daniel Cremers |
| Tutorial&Exercise | Thursdays, 10:00-12:00 | Online | TA Team |
Lectures: Live streamed and recorded automatically via TUM-Live: https://live.rbg.tum.de/
Tutorials: Pre-recorded, uploaded every Thursday, 10:00 AM.
Exercises: Mostly coding, jupyter-notebooks and Python based, uploaded every Thursday, 10:00 AM.
Period: 15.10.2024 - 06.02.2025
Language: English
ECTS: 6
SWS: 4
Prerequisites
- Strong mathematical background: linear algebra, calculus.
- Previous knowledge of Python, including scripting skills such as operating system calls.
- Machine Learning background.
Registration
If you plan to attend, please register for the course on TUMonline. Later during the semester, you will have to register for the exam.
For students who cannot register via TUMonline, please fill in this form: https://forms.gle/x2gR9hXayAhiLFJ5A.
Announcements and Discussions
We use Piazza instead of Moodle. Please join the class via the link: https://piazza.com/tum.de/fall2024/in2346ws2425.
Lectures
| Date | Slides | Recording |
|---|---|---|
| 15.10 | Lecture 01: Introduction | Lecture 01 |
| 22.10 | Lecture 02: Machine Learning Basics | Lecture 02 |
| 29.10 | Lecture 03: Introduction to Neural Networks | Lecture 03 |
| 05.11 | Lecture 04: Optimization and Backpropagation | Lecture 04 |
| 12.11 | Lecture 05: Scaling Optimization | Lecture 05 |
| 19.11 | Lecture 06: Training Neural Networks | Lecture 06 |
| 26.11 | Lecture 07: Loss Functions and Activations | Lecture 07 |
| 03.12 | Lecture 08: Augmentation and Regularization | Lecture 08 |
| 10.12 | Lecture 09: Convolutional Neural Networks | Lecture 09 |
| 17.12 | Lecture 10: CNN Architectures | Lecture 10 |
| 07.01 | Lecture 11: RNNs and Transformers | Lecture 11 |
| 14.01 | Guest Lecture | |
| 21.01 | Lecture 12: Advanced Deep Learning Topics | Lecture 12 (Part 1) |
| 28.01 | Research Projects in Computer Vision Group | |
| 04.02 | Lecture 12 (Part 2) |
Tutorials and Exercises
Final Exam and Credits
The final exam will be on 12 Feb 2025, 16:30 - 18:00. The exam will most likely be a traditional onsite exam, so please take this into consideration if you intend to receive credits for this class. Credits are only awarded to students who participated and successfully passed the exam.
As this course is taught every semester, there will be no retake exam; you will have to take next semester's exam (bonus will be transferred).
We provide a mock exam and the solution for your reference.
Contact
Please refrain from sending us emails individually. You can contact us for individual regards through the email: i2dl@vision.in.tum.de. All TAs of the course will receive these emails.
