Différences entre les versions de « Deep Learning Tutorial 2019 »
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<center><div align="center" style="border:2px solid black; background:#fef6e7; color:blue; align:center; width:30%" > Registration deadline: July 7, 2019</div></center> | <center><div align="center" style="border:2px solid black; background:#fef6e7; color:blue; align:center; width:30%" > Registration deadline: July 7, 2019</div></center> | ||
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− | !colspan="2"| <b style="font-size:150%">Scope</b><hr> | + | !colspan="2"| <b style="font-size:150%">Scope</b><hr> |
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| valign="top" style="font-size:110%"|<p>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.<br></p><br> | | valign="top" style="font-size:110%"|<p>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.<br></p><br> | ||
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* Deep learning libraries installable via the ''Installations'' menu | * Deep learning libraries installable via the ''Installations'' menu | ||
* Training dataset downloadable from the ''Installations'' menu | * Training dataset downloadable from the ''Installations'' menu | ||
− | + | mediation date: TBA | |
− | + | <p>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. | |
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! style="background:lightblue;color:black;font-width:bold;text-align:center;border-bottom:1.5px solid black" |Speaker | ! style="background:lightblue;color:black;font-width:bold;text-align:center;border-bottom:1.5px solid black" |Speaker | ||
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− | | width= | + | | width=11% | 09:00 - 10:00 |
− | | width= | + | | width=28% | Introduction to deep learning concepts |
| width=10% | Nicolas Padoy | | width=10% | Nicolas Padoy | ||
− | | width= | + | | width=11% | 09:00 - 11:00 |
− | | width= | + | | width=28% | Introduction to TensorFlow |
| width=10% | Armine Vardazaryan | | width=10% | Armine Vardazaryan | ||
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||Introduction to PyTorch | ||Introduction to PyTorch | ||
||Vinkle Srivastav | ||Vinkle Srivastav | ||
− | ||14:00-15:00 | + | ||14:00 - 15:00 |
||Inference with state-of-the-art models in TensorFlow (part 2) | ||Inference with state-of-the-art models in TensorFlow (part 2) | ||
||Chinedu Nwoye | ||Chinedu Nwoye | ||
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<b style="font-size:150%">General Information</b><hr> | <b style="font-size:150%">General Information</b><hr> | ||
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| valign="top"| <b><br><big>News</big></b><br> | | valign="top"| <b><br><big>News</big></b><br> | ||
* [ <i style='color:blue'>10/06/2019</i> ]: Registration for the DSAI deep learning tutorial is open. | * [ <i style='color:blue'>10/06/2019</i> ]: Registration for the DSAI deep learning tutorial is open. |
Version du 7 juin 2019 à 22:28
DSAI DEEP LEARNING TUTORIAL
Registration | Syllabus | Installations | Contacts |
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:
mediation date: TBA 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.
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Date & Venue | |
Date : Time : Venue : |
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 | |
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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 | Unistra HPC (to confirm) | TBA | 15:30 - 17:30 | TBA | Thomas Lampert |
Speakers
Nicolas Padoy
Professor
University of Strasbourg.
websiteChinedu Nwoye
PhD Student
University of Strasbourg.
websiteTong Yu
PhD Student
University of Strasbourg.
websiteArmine Vardazaryan
Research Engineer
University of Strasbourg.
websiteVinkle Kumar Srivasta
PhD Student
University of Strasbourg.
websiteThomas Lampert
Post-doc Researcher
University of Strasbourg.
websiteHPC Representative
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University of Strasbourg.
website
General Information
News
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Contacts us Send your questions to this email and we will get back to you. Board Email: dltutorialboard.dsai@icube.unistra.fr |