Module Handbook

  • Dynamischer Default-Fachbereich geändert auf INF

Course INF-71-56-K-6

Applications of Machine Learning and Data Science (2V+1U, 4.0 LP)

Course Type

SWS Type Course Form CP (Effort) Presence-Time / Self-Study
- K Lecture with exercise classes (V/U) 4.0 CP 78 h
2 V Lecture 28 h
1 U Exercise class (in small groups) 14 h
(2V+1U) 4.0 CP 42 h 78 h

Basedata

SWS 2V+1U
CP, Effort 4.0 CP = 120 h
Position of the semester 1 Sem. in WiSe
Level [6] Master (General)
Language [EN] English
Lecturers
Area of study [INF-KI] Intelligent Systems
Livecycle-State [NORM] Active

Possible Study achievement

  • Verification of study performance: proof of successful participation in the exercise classes (ungraded)
  • Details of the examination (type, duration, criteria) will be announced at the beginning of the course.

Contents

  • Approaches for analysing and explaining Time Series
  • Time Series Forecasting and Neural Architecture Search
  • Smart Grid Monitoring and Assessment
  • Attention-Based Natural Language Processing
  • Natural Language Generation
  • Meta-Learning or Learning to Learn
  • Adversarial attacks and Links to Interpretability
  • Video Object Segmentation
  • The intricacies of scaling in neural network training
  • Knowledge Graph Construction
  • Self-organizing Personal Knowledge Assistants

Literature

  • Friedman, Jerome, Trevor Hastie, and Robert Tibshirani. The elements of statistical learning. Vol. 1. No. 10. New York: Springer series in statistics, 2001.
  • Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. Deep learning. MIT press, 2016.
  • Dengel, Andreas, Semantische Technologien – Grundlagen. Konzepte. Technologien. Spektrum Akademischer Verlag, Springer Berlin Heidelberg (Oct. 2011), 427 pages (in German).

Requirements for attendance (informal)

None

Requirements for attendance (formal)

None

References to Course [INF-71-56-K-6]

Module Name Context
[INF-71-56-M-6] Applications of Machine Learning and Data Science P: Obligatory 2V+1U, 4.0 LP
[SO-14-116--M-6] Application of intelligent systems WP: Obligation to choose 2V+1U, 4.0 LP
Course-Pool Name
[INF-KI_V-KPOOL-6] Lectures of the teaching area Intelligent Systems
[INF-SI_Inf_IntSys-KPOOL-7] Intelligent Systems