392119 Übungen zu Vertiefung Maschinelles Lernen (Ü) (WiSe 2023/2024)

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Aufbauend auf dem Grundlagen-Modul "Neuronale Netze und Lernen", welches die grundlegende Theorie des maschinellen Lernens sowie einige grundlegende Ansätze behandelt hat, werden in diesem Modul thematische Vertiefungen zu folgenden Themenfeldern behandelt: Repräsentationen, Transformer-Architekturen für Sequenzen, Generative Modelle (Autoregressiv und GAN), Neuronaler Computer, Reinforcement-Lernverfahren, Ausgewählte Theorieaspekte, Learning to Learn (Meta-L, One/Few-Shot-L), Ausblick und aktuelle Trends.

Building on lecture "Neuronale Netze und Lernen" this module offers advanced methods in these topic areas: representations, sequence-to-sequence transformer architectures, generative models (autoregressive and GAN), neural computer, reinforcement learning methods, selected theory aspects, learning-to-learn (meta-L,one/few-shot L), outlook and current trends.

Requirements for participation, required level

Die Vorlesung wendet sich an einschlägig interessierte Studenten der Informatik, Mathematik und Linguistik im Hauptstudium. Neuronale Netze und Lernen

External comments page

http://www.zfl.uni-bielefeld.de/studium/module/techfak/msc_isy/#vertiefung_maschinelles_lernen

Teaching staff

Dates ( Calendar view )

Frequency Weekday Time Format / Place Period  
wöchentlich Fr 8-10 X-E0-220 09.10.2023-02.02.2024
not on: 10/13/23 / 10/20/23 / 11/3/23 / 12/29/23 / 1/5/24
einmalig Di 08-10 X-E0-220 06.02.2024
einmalig Do 08-10 X-E0-218 02.05.2024 Übungen von 08:30 - 10 Uhr

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Subject assignments

Module Course Requirements  
39-M-Inf-AI-adv-foc_ver1 Advanced Artificial Intelligence (focus) Advanced Artificial Intelligence (focus): Übung (Alternative) Student information
39-M-Inf-AI-bas Basics of Artificial Intelligence Basics of Artificial Intelligence: Übung (Alternative) Student information
39-M-Inf-VML Vertiefung Maschinelles Lernen Vertiefung Maschinelles Lernen Ungraded examination
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.


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E-Learning Space
E-Learning Space
Limitation of the number of participants:
Limited number of participants: 35
Address:
WS2023_392119@ekvv.uni-bielefeld.de
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Last update basic details/teaching staff:
Wednesday, August 2, 2023 
Last update times:
Tuesday, April 30, 2024 
Last update rooms:
Tuesday, April 30, 2024 
Type(s) / SWS (hours per week per semester)
Übung (Ü) / 1
Department
Technische Fakultät
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ID
426069659