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	Lecture 13A : The ups and downs of backpropagation (Blitz Kim) View
	Lecture 13.1 — The ups and downs of backpropagation [Neural Networks for Machine Learning] (Colin McDonnell) View
	Lecture 13.1 — The ups and downs of backpropagation — [ Deep Learning \| Geoffrey Hinton \| UofT ] (Artificial Intelligence - All in One) View
	Lecture 13B : Belief Nets (Blitz Kim) View
	Lecture 10.3 — The idea of full Bayesian learning — [ Deep Learning \| Geoffrey Hinton \| UofT ] (Artificial Intelligence - All in One) View
	Lecture 15A : From Principal Components Analysis to Autoencoders (Blitz Kim) View
	Lecture 12E : RBMs for collaborative filtering (Blitz Kim) View
	Lecture 7A : Modeling sequences: A brief overview (Blitz Kim) View
	Lecture 3.1 — Learning the weights of a linear neuron [Neural Networks for Machine Learning] (Colin McDonnell) View
	Lecture 2.4 — Why the learning works — [ Deep Learning \| Geoffrey Hinton \| UofT ] (Artificial Intelligence - All in One) View