Deep Learning


The goal is to enable the students to understand the fundamental Deep Learning algorithms for large datasets. To this end, the theory of these algorithms is developed in the lectures and during the practice sessions, many such data sets are analyzed.

Kurse in diesem Modul

Deep Learning:
  • Review Linear Algebra, Probability and Numerical Computation
  • Machine Learning Basics
  • Deep Feedforward Networks
  • Regularization for Deep Learning
  • Optimization for Training Deep Models
  • Convolutional Networks
  • Sequence Modeling
  • Practical Methodology

The module is based on the excellent book: "Deep Learning" by Ian Goodfellow, Yoshua Bengio and Aaron Courville.The book also has a useful website:

Vorlesung mit 2 Lektionen pro Woche
Praktikum mit 2 Lektionen pro Woche

Diese Beschreibung ist rechtlich nicht verbindlich! Weitere Informationen finden Sie in der detaillierten Modulbeschreibung.