Deep Learning School

Here you can watch lectures from the 2016 Deep Learning Summer School in Montreal.

Course excerpt:

Deep neural networks that learn to represent data in multiple layers of increasing abstraction have dramatically improved the state-of-the-art for speech recognition, object recognition, object detection, predicting the activity of drug molecules, and many other tasks. Deep learning discovers intricate structure in large datasets by building distributed representations, either via supervised, unsupervised or reinforcement learning.

The Deep Learning Summer School 2016 is aimed at graduate students and industrial engineers and researchers who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning) and wish to learn more about this rapidly growing field of research.

Here is the schedule in which you could view the presentations

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01/08/2016	02/08/2016	03/08/2016	04/08/2016	05/08/2016	06/08/2016	07/08/2016
9:00 10:30	Doina Precup Machine Learning	Rob Fergus Introduction to CNNs	Yoshua Bengio RNNs	Kyunghyun Cho Natural Language Understanding	Joelle Pineau Reinforcement Learning	Ruslan Salakhutdinov Deep Generative Models I	Bruno Olshausen Comp. Neuro I
10:30 11:00	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break
11:00 12:30	Hugo Larochelle Neural Networks I	Antonio Torralba Learning to See	Sumit Chopra Attention and Memory	Edward Grefenstette Beyond Seq2Seq	Pieter Abbeel Deep RL	Shakir Mohamed Building Machines that Imagine and Reason	Surya Ganguli Comp. Neuro II and Deep Learning Theory
12:30 14:30	Lunch	Lunch	LunchWiDL event	Lunch	Lunch	Lunch	Lunch
14:30 16:00	Hugo Larochelle Neural Networks II (click on part II)	Alex Wiltschko Torch I	Jeff Dean Large Scale Deep Learning & TensorFlow	Julie Bernauer (NVIDIA) GPU programming with CUDA	Joelle, Pieter & Doina Advanced Topics in RL	Contributed talks Session 4	Contributed talks Session 4
16:00 16:30	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break
16:30 18:00	Pascal Lamblin Theano I	Practical Session Alex Wiltschko (Torch) Frédéric Bastien (Theano)	Jeff Dean Large Scale Deep Learning & TensorFlow (click on part II)	Contributed talks Session 1	Contributed talks Session 2	Contributed Posters Session 1	Contributed Posters Session 2
Evening	Opening Reception (18:00-20:30) — by — Imagia	Happy Hour (18:45-22:30) buses at 18:30 — by — Maluuba	Happy Hour (18:30-20:30) — by — Creative Destruction Lab

(or you can just follow them in consecutive order at http://videolectures.net/deeplearning2016_montreal/ since they seem to be in the order they were presented.)