Very Deep Learning - Recent Methods and Technologies

In this lecture the most recent advances of deep learning will be presented.

The intended schedule is:

  • Introduction, Motivation
  • Advanced Convolutional Networks (ConvNet, AlexNet, GoogLeNet)
  • SqueezeNet
  • Extended Recurrent Neural Networks (LSTM, MD-LSTM, Dynamic Cortex Memories)
  • Spiking Neural Networks
  • Reinforcement Learning (Policy and Value Networks)
  • Bleeding-Edge Architectures (depending on the most recent publications in Deep Learning).
     
Learning Outcomes: 

Expected outcomes:

  • Understanding and Implementing advanced deep learning methods
  • Solving difficult tasks in Pattern Recognition, Data Science, and Big Data Analytics Literatur
     
Type: 
Course
Semester: 
A2017
ECTS: 
5
Lecturer: 
Site: 
F
Code: 
33092
63092
Language: 
english
Period: 
weekly
Schedule: 
Thursday: 14:15 - 17:00
Location: 
UniFR, PER21
Room: 
D230
Comment: 

First Lecture
The first lecture will take place on Thursday, 28.09.2017 at 14:15 in UniFR, PER21, room D230.

ILIAS
The course page in ILIAS can be found at https://ilias.unibe.ch/goto.php?target=crs_1166733&client_id=ilias3_unibe.