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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
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 external students who cannot register via TUMonline, please fill in this form: https://forms.gle/x2gR9hXayAhiLFJ5A.
Anouncements and Discussions
We use Piazza instead of Moodle. Please join the class via the link: https://piazza.com/tum.de/fall2024/in2346ws2425.
Materials and Videos
Slides and recording:
TBA
Tutorials and exercises:
TBA
Final Exam and Credits
The final exam will be on TBD. 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.
