Deep Learning Tutorial 2019
DSAI DEEP LEARNING TUTORIAL
| Registration | Installations |
| Scope | |
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The Data science and artificial intelligence (DSAI) research axis of ICube offers a two-day tutorial targeting researchers from all scientific backgrounds interested in the fast developing area of deep learning from a practical standpoint. The purpose of this event is to help participants build up the basic skillset necessary for understanding, training and running deep neural networks that may benefit their respective research activities. A wide array of topics will be covered with a heavily hands-on approach - from fundamental concepts and programming skills to state-of-the-art deep learning libraries and models - through a series of practicals, given by experienced PhD students and researchers. The tutorial will introduce participants to the libraries using Jupyter notebooks and help researchers desiring to apply DSAI approaches to analyze their data, such as images, videos, text, etc. ICube researchers with interest in deep learning are hereby encouraged to join the tutorial by subscribing via the registration link. |
 
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| Participation Pre-requisites | |
| Participation is by registration. Limited space is available and the slots are given on a first come first serve basis.
In addition, a participant needs the following:
If you have hitches in accessing any file or completing the necessary installations before the program days, keep on watching this space, a date will be announced later to resolve all preparatory installation issues.
Help session date: Thursady 26th September, 2019. Time: 8:30AM - 8:59AM | |
Date & Venue | |
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Date : Time : Venue : |
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| Program |
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The courses will run for 2 days. Participants will be able to attend both sessions. The detailed syllabus will be accessible via link on the menu bar. However, an abridge form is presented as follows: |
| Day 1 | Day 2 | |||||
| Time | Topic | Speaker | Time | Topic | Speaker | |
|---|---|---|---|---|---|---|
| 09:00 - 10:00 | Introduction to deep learning concepts | Nicolas Padoy | 09:00 - 11:00 | Introduction to TensorFlow | Armine Vardazaryan | |
| 10:00 - 10:30 | Coffee Break | 11:00 - 11:30 | Coffee Break | |||
| 10:30 - 12:30 | A primer on Python for deep learning | Tong Yu | 11:30 - 12:30 | Inference with state-of-the-art models in TensorFlow (part 1) | Chinedu Nwoye | |
| 12:30 - 14:00 | Break/Lunch | 12:30 - 14:00 | Break/Lunch | |||
| 14:00 - 16:00 | Introduction to PyTorch | Vinkle Srivastav | 14:00 - 15:00 | Inference with state-of-the-art models in TensorFlow (part 2) | Chinedu Nwoye | |
| 16:00 - 16:30 | Coffee Break | 15:00 - 15:30 | Coffee Break | |||
| 16:30 - 17:30 | Presentation of Unistra HPC | Vincent Lucas | 15:30 - 17:30 | Generating images with GANs | Thomas Lampert | |
Speakers
Nicolas Padoy
Professor
University of Strasbourg.
website
Chinedu Nwoye
PhD Student
University of Strasbourg.
website
Tong Yu
PhD Student
University of Strasbourg.
website
Armine Vardazaryan
Research Engineer
University of Strasbourg.
website
Vinkle Kumar Srivasta
PhD Student
University of Strasbourg.
website
Thomas Lampert
Post-doc Researcher
University of Strasbourg.
website
Vincent Lucas
HPC Representative
University of Strasbourg.
website
General Information
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