Category - Geoffrey Hinton

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 9.1 — Overview of ways to improve generalization [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 8.4 — Echo State Networks [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 8.3 — Predicting the next character using HF [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 8.2 — Modeling character strings [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 8.1 — A brief overview of Hessian-free optimization [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 7.5 — Long term Short term memory [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 7.4 — Why it is difficult to train an RNN? [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 7.3 — A toy example of training an RNN [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 7.2 — Training RNNs with back propagation [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 1.3 — Some simple models of neurons [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 6.5 — Rmsprop: normalize the gradient [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 6.4 — Adaptive learning rates for each connection [Neural Networks for Machine Learning]