Table of Contents
Introduction to PyTorch for (Data) Scientists
Date
- 15 April, 2025
- 9:00 am - 1:00 pm
Venue
- Building 1, Level 2, Multi-purpose Room (MPR) (Desert Side)
Organizer
Didier Barradas Bautista
Visualization Core Laboratory
didier.barradasbautista@kaust.edu.sa
Register
How to Prepare?
- Here is the material we will follow : PyTorch.
- As alternative, read the material here : Learn PyTorch for Deep Learning: Zero to Mastery book.
- Local Setup : Here.
- KAUSTians you will be able to use:
- After you create the GitHub account, get access here
- JupyterHub, use your portal credentials to log in
Overview
PyTorch is an open-source deep learning framework developed by Facebook's AI Research Lab (FAIR). It is widely used for building and training neural networks due to its flexibility and ease of use. Learning PyTorch is beneficial because it is one of the most popular artificial intelligence and machine learning frameworks. It is extensively used in academia and industry, powering applications from simple image classifiers to complex systems like self-driving cars and large language models.
This hands-on lesson is part of the Introduction to Data Science Workshop Series offered by KVL as part of our ongoing efforts to build core data science skills capacity both at KAUST and within the Kingdom of Saudi Arabia (KSA).
If you have any questions, please contact us at help@vis.kaust.edu.sa.
Who Should Attend?
The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.
Agenda
| Time | Topic |
|---|---|
| 09:00 | Introduction to PyTorch |
| 09:30 | Autograd: Automatic Differentiation |
| 10:00 | Building Neural Networks |
| 11:00 | Training a Model on a Dataset |
| 12:00 | Advanced Topics |