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Deep Learning Summer School 2016 - Montreal   

Deep Learning Summer School, Montreal 2016

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.


Invited Talks

Contributed Talks

Reviews and comments:

Comment1 nastaran, November 20, 2016 at 5:09 p.m.:

Dissertation or article (missing values in microarray DNA of the gene ontology clustering neural network convolution) like. Please help me.

Comment2 Katie Hayes, April 28, 2020 at 8:49 a.m.:

Comment3 goku, July 10, 2020 at 5:14 a.m.:

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