Hinton

/videos/Neural Networks for Machine Learning 5.1 A bag of tricks for mini-batch gradient descent.mp4

/videos/Neural Networks for Machine Learning 5.0 Overview of mini-batch gradient descent.mp4

/videos/Neural Networks for Machine Learning 3.1 A brief diversion into cognitive science.mp4

/videos/Neural Networks for Machine Learning 1.2 A geometrical view of perceptrons.mp4

/videos/Neural Networks for Machine Learning 2.1 The error surface for a linear neuron.mp4

/videos/Neural Networks for Machine Learning 6.3 Why it is difficult to train an RNN.mp4

/videos/Neural Networks for Machine Learning 11.2 Restricted Boltzmann Machines.mp4

/videos/Neural Networks for Machine Learning 4.1 Achieving viewpoint invariance.mp4

/videos/Neural Networks for Machine Learning 6.2 A toy example of training an RNN.mp4

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

/videos/Neural Networks for Machine Learning 1.0 Types of neural network architectures.mp4

/videos/Neural Networks for Machine Learning 4.0 Why object recognition is difficult.mp4

/videos/Neural Networks for Machine Learning 5.3 Adaptive learning rates for each connection.mp4

/videos/Neural Networks for Machine Learning 14.5 Shallow autoencoders for pre-training.mp4

/videos/Neural Networks for Machine Learning 11.4 RBMs for collaborative filtering.mp4

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