Difference between revisions of "History of Computers - Deep Learning"

Revision as of 23:07, 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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