Supercomputing platforms and Frameworks for Deep Learning
Part I of DLAI-MET Master Course at UPC (Autumn 2017)
Official Course Web Site
Office: Mòdul C6- 217 (second floor)
Teaching Assistants :
PhD candidate on Neural Machine Translation
Research Computer Engineer at BSC
Description: This part of DLAI course will briefly present the basic computational requirements and popular frameworks for DL.
Previous knowledges Prior exposure to programming in Python and experience with Linux basics will be helpful.
Content of this part:
- Lecture 1 – Why Supercomputing matters to Deep Learning (Slides) (class notes 1 and class notes 2)
- Lecture 2 – KERAS basics (slides) (class notes)
- Lecture 4 – PyTorch Basics (slides)
- Lab 1 – Getting Started with DLAI labs
- Lab 3 – First steps with Keras
Class handouts and materials associated with this class can be found on the Atenea intranet or through the links on this page.
This page and its links will be updated throughout this course to keep the information as updated as possible. (last modified 21/October/2017)