Machine Learning 2013

These are the lectures for a machine learning course taught by Nando de Freitas at UBC in 2013.

			Machine learning - introduction by Nando de Freitas			59:58
			Machine learning - linear prediction by Nando de Freitas			1:04:20
			Machine learning - Maximum likelihood and linear regression by Nando de Freitas			1:14:01
			Machine learning - Regularization and regression by Nando de Freitas			1:01:16
			Machine learning - regularization, cross-validation and data size by Nando de Freitas			58:47
			Machine learning - Bayesian learning by Nando de Freitas			1:17:40
			Machine learning - Bayesian learning part 2 by Nando de Freitas			21:10
			Machine learning - Introduction to Gaussian processes by Nando de Freitas			1:18:55
			Machine learning - Gaussian processes by Nando de Freitas			1:17:28
			Machine learning - Bayesian optimization and multi-armed bandits by Nando de Freitas			1:20:30
			Machine learning - Decision trees by Nando de Freitas			1:06:06
			Machine learning - Random forests by Nando de Freitas			1:16:55
			Machine learning - Random forests applications by Nando de Freitas			51:42
			Machine learning - Unconstrained optimization by Nando de Freitas			1:16:19
			Machine learning - Logistic regression by Nando de Freitas			1:13:47
			Machine learning - Logistic regression by Nando de Freitas			1:13:47
			Machine learning - Neural networks by Nando de Freitas			1:04:24
			Machine learning - Deep learning I by Nando de Freitas			1:15:05
			Machine learning - Deep learning II, the Google autoencoders and dropout by Nando de Freitas			1:12:03
			Machine learning - Importance sampling and MCMC I by Nando de Freitas			1:16:18
			Machine learning - Markov chain Monte Carlo (MCMC) II by Nando de Freitas			39:17

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Machine Learning 2013

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