Basics of probability and statistics thumbnail
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Chapter list

Basics for Statistical Machine Learning Linear Algebra Basics00:00
Outline00:29
Motivation - 100:46
Concrete Example: Regression00:47
Concrete Example: Classification02:28
Concrete Example: Density Estimation / Clustering03:51
Motivation - 205:21
Linear Algebra Basics06:38
Vectors - 106:56
Vectors - 207:42
Matrices - 108:58
Matrices - 209:26
Matrices - 309:43
Matrices - 409:46
Matrices - 510:02
Matrices - 610:06
Matrices - 710:07
Matrices - 810:08
Matrices - 910:16
Matrices - 1010:32
Matrices - 1111:18
Matrices - 1211:27
Matrices - 1311:30
Matrices - 1411:33
Matrices - 1512:09
Determinant12:54
Inverses14:22
Determinants and Inverses - 115:33
Determinants and Inverses - 215:53
Matrices - 1616:24
Matrix Diagonalization19:32
Singular Value Decomposition27:57