DEEP-EST Tutorial: Introduction to Deep Learning

Tutorial under the umbrella of the DEEP-EST EU Project
Juelich Supercomputing Centre, Germany
2018-06-06 – 2018-06-07
[ Event ]

Materials

[ Lecture 1 – Introduction to Deep Learning – Slides ~3.29 MB (pdf) ]

[ Lecture 2 – Fundamentals of Convolutional Neural Networks (CNNs) – Slides ~3.81 MB (pdf) ]

[ Lecture 3 – Deep Learning in Remote Sensing: Challenges – Slides ~8.11 MB (pdf) ]

[ Lecture 4 – Deep Learning in Remote Sensing: Applications – Slides ~1.98 MB (pdf) ]

[ Lecture 5 – Model Selection and Regularization – Slides ~1.78 MB (pdf) ]

[ Lecture 6 – Fundamentals of Long Short-Term Memory (LSTM) – Slides ~3.74 MB (pdf) ]

Lecture 7 – LSTM Applications and Challenges
(cancelled due to time problems during the tutorial)

Lecture 8 – Deep Reinforcement Learning
(online shortly, slides have been requested, pending)

Thanks to all participants of our Introduction to Deep Learning course organized by our DEEP-EST project @DEEPprojects & Juelich Supercomputing Centre @fzj_jsc & University of Iceland @Haskoli_Islands – slides are publicly available at: https://t.co/c7BksTuC9b – CU next time! pic.twitter.com/Vk7cbVPPFb

— Morris Riedel (@MorrisRiedel) June 8, 2018

Day One of our Introduction to Deep Learning Tutorial organized by @DEEPprojects & @fzj_jsc & @Haskoli_Islands; Ernir Erlingsson @ernire gave a great introduction with convoluational neural networks & Gabriele Cavallaro describes challenges using deep learning in remote sensing pic.twitter.com/pG5Mtz1NVv

— Morris Riedel (@MorrisRiedel) June 7, 2018