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source: Nando de Freitas 2015年3月15日
Slides available at: https://www.cs.ox.ac.uk/people/nando....
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
More information here: http://www.cs.ox.ac.uk/teaching/courses/2014-2015/ml/
16: Reinforcement learning and neuro-dynamic programming 56:04
15: Deep Reinforcement Learning - Policy search 54:40
14: Karol Gregor on Variational Autoencoders and Image Generation 43:18
13: Alex Graves on Hallucination with RNNs 53:59
2: linear models 48:01
3: Maximum likelihood and information 1:12:59
4: Regularization, model complexity and data complexity (part 1) 40:27
5: Regularization, model complexity and data complexity (part 2) 58:58
6: Optimization 58:19
8: Modular back-propagation, logistic regression and Torch 52:56
7: Logistic regression, a Torch approach 44:31
9: Neural networks and modular design in Torch 53:47
10: Convolutional Neural Networks 50:30
12: Recurrent Neural Nets and LSTMs 51:10
11: Max-margin learning, transfer and memory networks 58:50
1: Introduction 52:16
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