392221 Deep Learning (V) (SoSe 2024)

Contents, comment

The lecture introduces the basic concepts of deep learning, covering the basic architectures, generative models, attacks and defebses, XAI methods, and structure processing models. Popular applications such as for image recognition will be discussed. On a practical side,mostly PyTorchwill be used.

Requirements for participation, required level

programming skills, mathematics, basics of machine learning or neural networks

Teaching staff

Dates ( Calendar view )

Frequency Weekday Time Format / Place Period  

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Subject assignments

Module Course Requirements  
39-M-Inf-AI-adv-foc Advanced Artificial Intelligence (focus) Advanced Artificial Intelligence (focus): Vorlesung Graded examination
Student information
39-M-Inf-AI-app Applied Artificial Intelligence Applied Artificial Intelligence: Vorlesung Student information
- Graded examination Student information
39-M-Inf-AI-app-foc Applied Artificial Intelligence (focus) Applied Artificial Intelligence (focus): Vorlesung Student information
- Graded examination Student information
39-M-Inf-DL Deep Learning Deep Learning Graded examination
Student information

The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.


Students are able distinguish different key architectures for deep learning, and they know the learning scenarios where these architectures can be used. The students know how to train a deep architecture, both, as regards the algorithmic pipeline and possible forms of implementation using modern systems.

E-Learning Space

A corresponding course offer for this course already exists in the e-learning system. Teaching staff can store materials relating to teaching courses there:

Registered number: 72
This is the number of students having stored the course in their timetable. In brackets, you see the number of users registered via guest accounts.
Address:
SS2024_392221@ekvv.uni-bielefeld.de
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If the reference number is used for several courses in the course of the semester, use the following alternative address to reach the participants of exactly this: VST_452154377@ekvv.uni-bielefeld.de
Coverage:
72 Students to be reached directly via email
Notes:
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Last update basic details/teaching staff:
Friday, January 26, 2024 
Last update times:
Friday, March 8, 2024 
Last update rooms:
Friday, March 8, 2024 
Type(s) / SWS (hours per week per semester)
V / 2
Language
This lecture is taught in english
Department
Faculty of Technology
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ID
452154377