Difference between revisions of "History of Computers - Deep Learning"
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Revision as of 23:06, 17 September 2018
Deep Learning
Introduction
Deep Learning was invented by Geoffrey Hinton and is the next generation of Neural Networks.[1] “There are several types of Deep learning,deep neural networks, belief networks and recurrent networks.” [2]
Overview
[1]
While Neural Networks send data on a linear route through the hidden layer to the output layer, Deep Learning networks use multiple hidden layers to model high-level abstractions.[3] Each layer uses the output from the previous layer as its input. Deep Learning networks. These networks can learn in one of two ways, either supervised – such as image recognition where inputs need to be classified – or unsupervised – where the computer is searching for a pattern. [4]
Significance
Some of the notable uses of Deep Learning algorithms are drug synthesis, facial recognition, natural language processing and computer vision. [5]
Reference
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