Introduction to Deep Learning

General Information

Summer Semester 2021.

SWS: 3, ECTS: 5.

Available for master students from: Computational Science and EngineeringInformationssystemtechnikElektrotechnik, Communications Technology.

The course will be conducted in English.

The material of the course and all imporant infromation is available at https://moodle.uni-ulm.de/ .

Important: The course will take place electronically in the summer semester 2021. Please check on Moodle for instructions.

Objectives

The aim of the course is to acquire basic knowledge on deep learning. This includes classical neural network models and recent deep architectures. Topics such as convolutional neural networks, optimisation, regularisation, generative models, sequential models will be covered among others. In the exercise, the participants will implement some of the standard models for classification or regression, transfer learning, generative models and acquire knowledge on machine learning applications.

Participation

Background on linear algebra, calculus, optimisation and programming will be helpful.

There will be two hours lecture every week and two hour exercise almost every second week.

The registration is performed through https://campusonline.uni-ulm.de.

For further questions on the course, the students may contact the lecturer.

Exam: End of July / Beggining of August 2021.

Repetition Exam: September 2021.

Lecture Schedule

 
Date Time Room Topic Comments
19.04.2021 12:00 Online Introduction

 

26.04.2021 12:00 Online Machine learning basics (Part 1)  
03.05.2021 12:00 Online Machine learning basics (Part 2)  
10.05.2021 12:00 Online Feed-forward Networks and Backpropagation  
17.05.2021 12:00 Online Optimization  
24.05.2021 - - Bank Holiday  
31.05.2021 12:00 Online Regularization, Parameter Initialization, Normalization (Part 1)  
07.06.2021 12:00 Online Regularization, Parameter Initialization, Normalization (Part 2)  
14.06.2021 12:00 Online Convolutional Neural Networks  
21.06.2021 12:00 Online Modern Deep Architectures  
28.06.2021 12:00 Online AutoEncoders  
05.07.2021 12:00 Online Sequential Processing, Attention (Part 1)  
12.07.2021 12:00 Online Sequential Processing, Attention (Part 2)  
19.07.2021 12:00 Online Generative Models  
26.07.2021 12:00 Online Recap, Exam Q&A  
         
         
         
         
         
         

Exercise Schedule

Date Time Room Topic Comments
05.05.2021 14:00 Online Machine learning basics Zoom Q&A about exercise. Actual exercise is released two days earlier.
19.05.2021 14:00 Online Feed-forward Networks and Backpropagation Zoom Q&A about exercise. Actual exercise is released two days earlier.
02.06.2021 14:00 Online Optimization Zoom Q&A about exercise. Actual exercise is released two days earlier.
16.06.2021 14:00 Online Regularization, Parameter Initialization, Normalization Zoom Q&A about exercise. Actual exercise is released two days earlier.
23.06.2021 14:00 Online Convolutional Neural Networks Zoom Q&A about exercise. Actual exercise is released two days earlier.
07.07.2021 14:00 Online Autoencoders Zoom Q&A about exercise. Actual exercise is released two days earlier.
21.07.2021 14:00 Online Sequential Processing Zoom Q&A about exercise. Actual exercise is released two days earlier.

 

 

Lecturer

Jun.-Prof. Dr. rer. nat. Vasileios Belagiannis 
Raum: 41.2.214
Telefon: +49 (0)731 50 27004
E-Mail | Homepage

Exercise

Strohbeck Jan, M. Sc.
Raum: 41.2.216
Telefon: +49 (0)731 50 27026
E-Mail | Homepage

Schedule and Place

Lecture: Monday, 12:00 - 14:00 Uhr (Online)

Exercise: Monday (every second week), 14:00 - 16:00 Uhr (Online)