Fall 2020 / DM873 / DS809
Given the current situation with COVID, there might be constant change to schedule and format of the course. It looks like we will have the fist session on campus. Nevertheless, I will live stream the sessions as well (link will be found on blackboard) so students can decide whether they want to participate on campus or online.
This deep learning course runs with two course codes: DS809 and DM873. Since DS809 is a 5 ECTS course, it only constitutes of the first half of this course (till week 43). Therafter, the lectures will only be relevant for students taking DM873.
Machine learning has become a part in our everydays life, from simple product recommendations to personal electronic assistant to self-driving cars. More recently, through the advent of potent hardware and cheap computational power, “Deep Learning” has become a popular and powerful tool for learning from complex, large-scale data.
In this course, we will discuss the fundamentals of deep learning and its application to various different fields. We will learn about the power but also the limitations of these deep neural networks. At the end of the course, the students will have significant familiarity with the subject and will be able to apply the learned techniques to a broad range of different fields.
Mainly, the following topics will be covered:
- feedforward neural networks
- recurrent neural networks
- convolutional neural networks
- backpropagation algorithm
- factor analysis