227-0085-59L  Projekte & Seminare: Hands-On Deep Learning

SemesterAutumn Semester 2022
LecturersR. Wattenhofer
Periodicityevery semester recurring course
Language of instructionEnglish
CommentCourse can only be registered for once. A repeatedly registration in a later semester is not chargeable.


AbstractThe category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
ObjectiveThe objective of this P&S is to expose students to both common and cutting-edge neural architectures and to build intuition about their inner working by the means of examples. Students learn about various network structures as building blocks and use them to solve worked examples and course challenges. After attending this course, students will be familiar with multi-layer perceptrons, convolutional neural networks, recurrent neural networks, transformer encoders, graph convolutional/isomorphism/attention networks, and autoencoders.
ContentThis P&S introduces deep learning through the PyTorch framework in a series of hands-on examples, exploring topics in computer vision, natural language processing, graph neural networks, and representation learning.
Lecture notesPython Notebooks will be distributed to students before every session.