February 07, 2024 - by CSCS
This course is intended as a quick introduction of fundamental concepts of deep learning, covering neural network basics, training methods, as well as a few examples of specific applications such as convolutional neural networks for computer vision and the transformer model for natural language processing.
More specifically, the following topics will be covered:
- Fundamentals of neural networks.
- Training deep learning models: The stochastic gradient decent, optimizers, loss functions, regularization, etc.
- Convolutional Neural Networks (CNNs) for computer vision: Basics of CNNs. Image classification and generation.
- Natural Language Processing (NLP) with transformers: Basics of NLP, the transformer model, attention mechanism, etc.
The lessons will blend theory with hands-on practice, using PyTorch for practical exercises. We will run these sessions on the Piz Daint supercomputer at CSCS.
Target Audience: This course is intended for researchers who are starting to use deep learning in their work and would like a fast introduction to the field. The goal of the course is to provide the basic concepts and some pointers so the participants can continue their deep learning journey by themselves.
Deadline for registration: Wednesday, February 14, 2024
You can find more information and the registration form in the course webpage >
We look forward to welcoming you at CSCS!