Workshop / Overview
We start by introducing the basic building blocks (Tensors, Autograd) and also cover how to build more advanced models like CNNs or LSTMs in the second part.
During the workshop, we will go through a series of Jupyter notebooks which also allow participants to directly experiment with the code.
Workshop / Outcome
Acquire a solid understanding of the basics of PyTorch and get an overview of its powerful functionalities for deep learning applications.
Workshop / Difficulty
Workshop / Prerequisites
- Python Basics
- Machine Learning knowledge is not strictly necessary but we won't have time to explain all the machine learning details
- One laptop that can connect to Internet
Track / Co-organizers
A Conceptual Introduction to Reinforcement Learning
With Kevin Smeyers, Katrien Van Meulder & Bram Vandendriessche09:00-12:30 January 251ABC
Applied Machine Learning with R
With Dirk Wulff, Markus Steiner & Michael Schulte-Mecklenbeck09:00-17:00 January 25Foyer 6