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Mathematics for Machine Learning
English
Mathematics for Machine Learning
English
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Introduction to the Course
Resources
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Playlist (32 of 32 videos)
Playlist (32 of 32 videos)
1
Introduction to the Course
3:48
2
Statistics (video 1) - Statistics of Datasets
0:42
3
Statistics (video 2): Means
4:01
4
Statistics (video 3): Variances, Part 1/2
4:55
5
Statistics (video 4): Variances, Part 2/2
5:17
6
Statistics (video 5): Linear Transformations, Part 1/2
4:46
7
Statistics (video 6): Linear Transformations, Part 2/2
3:31
8
Statistics (video 7): Outro
0:28
9
Inner Products (video 1): Motivation
1:48
10
Inner Products (video 2): Dot Product
4:44
11
Inner products (video 3): Definition
5:03
12
Inner Products (video 4): Lengths and Distances, Part 1/2
7:08
13
Inner Products (video 5): Lengths and Distances, Part 2/2
3:43
14
Inner Products (video 6): Angles and Orthogonality
5:42
15
Inner Products (video 7): Unconventional Inner Products
7:23
16
Inner products (video 8): Outro
0:36
17
Projections (video 1): Motivation
0:41
18
Projections (video 2): Projection onto 1D Subspaces
7:43
19
Projections (video 3): Example 1D Projection
3:27
20
Projections (video 4): N-dimensional projections
8:34
21
Projections (video 5): Example N-dimensional Projections
3:53
22
Projections (video 6): Outro
0:33
23
PCA (video 1): Motivation
1:09
24
PCA (video 2): Setting
7:46
25
PCA (video 3): Optimal Coordinates
5:30
26
PCA (video 4): Reformulation of the Loss Function
10:26
27
PCA (video 5): Optimization of the Basis Vectors
7:40
28
PCA (video 6): Summary
4:08
29
PCA (video 7): PCA in High Dimensions
5:49
30
PCA (video 8): Other Perspectives of PCA
7:43
31
PCA (video 9): Outro
0:43
32
Outro Course
0:57
