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Fundamentals of Deep Learning for Computer Vision

30 Avr - 01 Mai 2018    Cargèse, France    Ecole Thématique

Objectifs

Le Centre de Calcul Régional ROMEO et NVIDIA proposent une formation dédiée au Deep Learning, les lundi 30 avril et mardi 1er mai 2018 à Institut d'Etudes Scientifiques de Cargèse. Cette formation formation fait suite aux deux premières formations d'initiations et est destinée à la fois aux universitaires et entreprises qui souhaitent découvrir le Deep Learning et en expérimenter les capacités dans un environnement NVIDIA / GDX-1.

L'ensemble aura lieu en Français, mais les contenus sont majoritairement disponibles en langue anglaise.

Contenu

Programme :
Présentation du Centre de Calcul ROMEO
Introduction to NVIDIA software et hardware for Deep Learning
Introduction to Deep Learning : du Neurone au Réseau de Neurone

In this hands-on course, you will learn the basics of deep learning by training and deploying neural networks.
Explore the fundamentals of deep learning by training neural networks and using results to improve performance and capabilities. In this hands-on course, you will learn the basics of deep learning by training and deploying neural networks. On completion, you will be able to solve your own problems with deep learning.

You will learn how to:
Implement common deep learning workflows, such as image classification and object detection.
Experiment with data, training parameters, network structure and other strategies to increase performance and capability.
Deploy your neural networks to start solving real-world problems.
After completing the course, you will receive a certificate.


Image Classification with DIGITS
Deep learning enables entirely new solutions by replacing hand-coded instructions with models learned from examples. Train a deep neural network to recognize handwritten digits by:
Loading image data to a training environment
Choosing and training a network
Testing with new data and iterating to improve performance
On completion of this Lab, you will be able to assess what data you should be training from.

Object Detection with DIGITS
Many problems have established deep learning solutions, but sometimes the problem that you want to solve does not. Learn to create custom solutions through the challenge of detecting whale faces from aerial images by: - Combining traditional computer vision with deep learning - Performing minor “brain surgery” on an existing neural network using the deep learning framework Caffe - Harnessing the knowledge of the deep learning community by identifying and using a purpose-built network and end-to-end labeled data. Upon completion of this lab, you will be able to solve unique problems with deep learning.


Neural Network Deployment with DIGITS and TensorRT
Deep learning allows us to map inputs to outputs that are extremely computationally intense. Learn to deploy deep learning to applications that recognize images and detect pedestrians in real time by:
Accessing and understanding the files that make up a trained model
Building from each function’s unique input and output
Optimizing the most computationally intense parts of your application for different performance metrics like throughput and latency
Upon completion of this Lab, you will be able to implement deep learning to solve problems in the real world.

Le planning, le programme et la liste des intervenants sont en cours de construction et non définitifs.

Prérequis

Le contenu des labs est en langue anglaise, mais l'échange avec les intervenants aura lieu en Français.

Entités contributrices

  • ROMEO
  • URCA

Contacts

Localisation

Adresse :
Institut d'Etudes Scientifiques, 20130 Cargèse, Corse, France