Module Handbook

  • Dynamischer Default-Fachbereich geändert auf INF

Module INF-75-60-M-6

Optimization for Deep Learning (M, 6.0 LP, AUSL)

Module Identification

Module Number Module Name CP (Effort)
INF-75-60-M-6 Optimization for Deep Learning 6.0 CP (180 h)

Basedata

CP, Effort 6.0 CP = 180 h
Position of the semester 1 Sem. in SuSe
Level [6] Master (General)
Language [EN] English
Module Manager
Lecturers
Area of study [INF-KI] Intelligent Systems
Reference course of study [INF-88.79-SG] M.Sc. Computer Science
Livecycle-State [AUSL] Phase-out period

Examination achievement PL1

  • Form of examination: oral examination (20-60 Min.)
  • Examination Frequency: Examination only within the course
  • Examination number: 67560 ("Optimization for Deep Learning")

Evaluation of grades

The grade of the module examination is also the module grade.


Competencies / intended learning achievements

After successfully completing the module, students will be able to:
  • understand various fundamental concepts and motivations for optimization in machine learning and deep learning
  • derive theoretical guarantees of optimization algorithms
  • develop and implement scalable optimization methods for deep learning
  • understand the balance between time and accuracy for important optimization methods

Requirements for attendance of the module (informal)

Mandatory requirements:
  • multivariable calculus and linear algebra (see module description of ML1 for details)
  • elementary probability (expectation, covariance matrices, variance, calculation rules, etc.)

Optional requirements (nice to have):

Requirements for attendance of the module (formal)

None

References to Module / Module Number [INF-75-60-M-6]