Hinton

/videos/Neural Networks for Machine Learning 13.0 Learning layers of features by stacking RBMs.mp4

/videos/Neural Networks for Machine Learning 3.0 Learning to predict the next word.mp4

/videos/Neural Networks for Machine Learning 2.0 Learning the weights of a linear neuron.mp4

/videos/Neural Networks for Machine Learning 12.2 Learning sigmoid belief nets.mp4

/videos/Neural Networks for Machine Learning 13.3 Modeling real-valued data with an RBM.mp4

/videos/Neural Networks for Machine Learning 8.1 Limiting the size of the weights.mp4

/videos/Neural Networks for Machine Learning 0.4 Three types of learning.mp4

/videos/Neural Networks for Machine Learning 14.4 Learning binary codes for image retrieval.mp4

/videos/Neural Networks for Machine Learning 2.2 Learning the weights of a logistic output neuron.mp4

/videos/Neural Networks for Machine Learning 9.3 Making full Bayesian learning practical.mp4

/videos/Neural Networks for Machine Learning 10.1 Dealing with spurious minima.mp4

/videos/Neural Networks for Machine Learning 7.2 Learning to predict the next character using HF.mp4

/videos/Neural Networks for Machine Learning 0.3 A simple example of learning.mp4

/videos/Neural Networks for Machine Learning 6.1 Training RNNs with back propagation.mp4

/videos/Neural Networks for Machine Learning 9.2 The idea of full Bayesian learning.mp4

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