Différences entre les versions de « Deep Learning Tutorial 2019 »
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<p>DSAI DL 2019 is a research tutorial event with a global scope aiming at introducing the participants to the basic concepts in the critical and fast developing area of deep learning. As part of the programs of the Data science and artificial intelligence (DSAI) research axis in ICube, the tutorial will help to prepare the participants with more efficient methods to deal with large-scale data in healthcare, computer vision, robotics, etc.</p><br /> | <p>DSAI DL 2019 is a research tutorial event with a global scope aiming at introducing the participants to the basic concepts in the critical and fast developing area of deep learning. As part of the programs of the Data science and artificial intelligence (DSAI) research axis in ICube, the tutorial will help to prepare the participants with more efficient methods to deal with large-scale data in healthcare, computer vision, robotics, etc.</p><br /> | ||
− | <p> | + | <p>Our foremost academics and PhD students will lecture and provide hands on practicals with the audience.</p> |
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+ | <p><i>Another intro...</i></p> | ||
+ | <p>The DSAI research axis of ICube offers a two-day tutorial targeting researchers from all scientific backgrounds interested in 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...</p> | ||
[[Image:Conv.jpg|frameless|450 px|right|Convolutional Neural Networks]]<br /> | [[Image:Conv.jpg|frameless|450 px|right|Convolutional Neural Networks]]<br /> |
Version du 7 juin 2019 à 11:13
DSAI DEEP LEARNING TUTORIAL
Registration | syllabus | Packages | Installations | Contacts |
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DSAI DL 2019 is a research tutorial event with a global scope aiming at introducing the participants to the basic concepts in the critical and fast developing area of deep learning. As part of the programs of the Data science and artificial intelligence (DSAI) research axis in ICube, the tutorial will help to prepare the participants with more efficient methods to deal with large-scale data in healthcare, computer vision, robotics, etc. Our foremost academics and PhD students will lecture and provide hands on practicals with the audience. Another intro... The DSAI research axis of ICube offers a two-day tutorial targeting researchers from all scientific backgrounds interested in 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... |
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Participation Pre-requisite | |||||||||||||||||||||||||||||||||||||||||||||||||
Participation is by registration. Limited space is available and the slot is 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 attend to this. |
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Date & Time: Venue: |
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Program The courses will run for 2 days. Participants will be able to attend both sessions. The detailed syllabus can be accessed via link on the menu bar. However, an abridge form is presented as follows: | |||||||||||||||||||||||||||||||||||||||||||||||||
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News | Contact us
Email: dltutorial.dsai@icube.unistra.fr Send your questions to this email and we will get back to you. |
correction:
- date and time to fix installations
- Intro writing
- jupyter notebooks
- experiment fundamental
- recommended to use laptop otherwise collab will be use