Category - Geoffrey Hinton

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 14.1 — Learning layers of features by stacking RBMs [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 13.4 — The wake sleep algorithm [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 13.3 — Learning sigmoid belief nets [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 13.1 — The ups and downs of backpropagation [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 3.1 — Learning the weights of a linear neuron [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 4.5 — Dealing with many possible outputs [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 4.4 — Neuro-probabilistic language models [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 4.3 — The softmax output function [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 4.2 — A brief diversion into cognitive science [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 4.1 — Learning to predict the next word [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 3.5 — Using the derivatives from backpropagation [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 3.3 — Learning weights of logistic output neuron [Neural Networks for Machine Learning]