392221 Deep Learning (V) (WiSe 2018/2019)
Contents, comment
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The lecture introduces the basic concepts of deep learning, in particular different popular architectures including restricted Boltzmann machines, convolutional neural networks, stacked autoencoders (as concerns feedforward models), and long short term memory models and recursive networks (as concerns recurrent models). Different tricks for training are introduced including optimiziation schemes such as ADAM, and training modi such as drop-out, and training set enhancement. Popular applications such as for image recognition will be discussed. On a practical side,mostly TensorFlow will be used with Keras as API.
Requirements for participation, required level
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Programmierkenntnisse (Python oder vergleichbar), Grundlagen Mathematik, Grundlagen maschinelles Lernen (etwa Neuronale Netze oder Einführung maschinelles Lernen)
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period |
|---|
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-Inf-AKS Anwendungen Kognitiver Systeme | Maschinelles Lernen im Web oder Modern Data Analysis oder Softcomputing für die Bioinformatik | Ungraded examination
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
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- Registered number: 125
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- WS2018_392221@ekvv.uni-bielefeld.de
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- 46 Students to be reached directly via email
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- Last update basic details/teaching staff:
- Monday, June 25, 2018
- Last update times:
- Monday, February 18, 2019
- Last update rooms:
- Monday, February 18, 2019
- Type(s) / SWS (hours per week per semester)
- lecture (V) / 2
- Language
- This lecture is taught in english
- Department
- Faculty of Technology
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