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Deep Learning - LeCun Bengio Hinton - Nature 2015 Article

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This is the article published by Lecun
Hinton and Bengion in
May 2015 in the journal Nature on the topic of deep learning.

doi:10.1038/nature14539

Summary:

Deep learning allows computational models that are composed of
multiple processing layers to learn representations of
data with multiple levels of abstraction. These methods have
dramatically improved the state-of-the-art in speech rec-
ognition, visual object recognition, object detection and
many other domains such as drug discovery and genomics. Deep
learning discovers intricate structure in large data
sets by using the backpropagation algorithm to indicate how a machine
should change its internal parameters that
are used to compute the representation in each layer from the representation in
the previous layer. Deep
convolutional nets have brought about breakthroughs in processing images, video, speech and
audio, whereas
recurrent nets have shone light on sequential data such as text and speech.
                                                             

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