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Stanford CS229M: Machine Learning Theory - Fall 2021

by Stanford Online · 20 videos

Total watch time

1d 4h 17m

at 1× speed · exactly 1 day, 4 hours, 16 minutes, 34 seconds at 1×

1×1d 4h 16m 34s
1.25×22h 37m 15s
1.5×18h 51m 3s
1.75×16h 9m 28s
2×14h 8m 17s
Average video1h 24m 50s
Longest1h 33m 1s
Shortest1h 4m 8s
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Videos (20)

1d 4h 17m in total · tick what you've watched

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Videos to
Watched
1 Stanford CS229M - Lecture 1: Overview, supervised learning, empirical risk minimization 1:04:08 2022-11-11
2 Stanford CS229M - Lecture 2: Asymptotic analysis, uniform convergence, Hoeffding inequality 1:20:14 2022-11-12
3 Stanford CS229M - Lecture 3: Finite hypothesis class, discretizing infinite hypothesis space 1:14:14 2022-11-13
4 Stanford CS229M - Lecture 4: Advanced concentration inequalities 1:31:17 2022-11-14
5 Stanford CS229M - Lecture 5: Rademacher complexity, empirical Rademacher complexity 1:23:59 2022-11-15
6 Stanford CS229M - Lecture 6: Margin theory and Rademacher complexity for linear models 1:22:41 2022-11-16
7 Stanford CS229M - Lecture 7: Challenges in DL theory, generalization bounds for neural nets 1:25:43 2022-11-17
8 Stanford CS229M - Lecture 8: Refined generalization bounds for neural nets, Kernel methods 1:27:11 2022-11-18
9 Stanford CS229M - Lecture 9: Covering number approach, Dudley Theorem 1:26:23 2022-11-19
10 Stanford CS229M - Lecture 10: Generalization bounds for deep nets 1:23:36 2022-11-20
11 Stanford CS229M - Lecture 11: All-layer margin 1:29:25 2022-11-21
12 Stanford CS229M - Lecture 13: Neural Tangent Kernel 1:29:30 2022-11-22
13 Stanford CS229M - Lecture 14: Neural Tangent Kernel, Implicit regularization of gradient descent 1:33:01 2022-11-23
14 Stanford CS229M - Lecture 15: Implicit regularization effect of initialization 1:24:14 2022-11-24
15 Stanford CS229M - Lecture 16: Implicit regularization in classification problems 1:29:52 2022-11-25
16 Stanford CS229M - Lecture 17: Implicit regularization effect of the noise 1:32:15 2022-11-26
17 Stanford CS229M - Lecture 18: Unsupervised learning, mixture of Gaussians, moment methods 1:22:08 2022-11-27
18 Stanford CS229M - Lecture 19: Mixture of Gaussians, spectral clustering 1:30:31 2022-11-28
19 Stanford CS229M - Lecture 20: Spectral clustering 1:28:25 2022-11-29
20 Stanford CS229M - Lecture 12: Non-convex optimization, Non-convex opt for PCA, matrix complexion 1:17:47 2022-12-09

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