Introduction to Deep Learning
Summer Semester 2020.
SWS: 3, ECTS: 5.
Available for master students from: Computational Science and Engineering, Informationssystemtechnik, Elektrotechnik, Communications Technology (at the moment).
The course will be conducted in English.
The material of the course and all imporant infromation is available at https://moodle.uni-ulm.de/ .
The aim of the course is to acquire basic knowledge on deep learning. This includes classical neural network models and recent 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.
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 2020.
Repetition Exam: September 2020.
|20.04.2020||12:00||43 / 43.2.104||Introduction|| |
|27.04.2020||12:00||43 / 43.2.104||Machine learning basics|
|04.05.2019||14:00||45 / 45.2.104 / PC-Pool 10||Extra place for laptop holders at 47 / 47.2.101|
Schedule and Place
Lecture: Monday, 12:00 - 14:00 Uhr (43.2.104)
Exercise: Monday (every second week), 14:00 - 16:00 Uhr (45.2.104)