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What is the Singular-Value Decomposition (SVD)?
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Classroom Contents
Principal Component Analysis - Lecture 8
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- 1 Introduction: Understanding data
- 2 Rank of a matrix
- 3 Matrix rank
- 4 Effect of noise
- 5 From images to data
- 6 Measuring data cloud "size" – using statistics
- 7 Measuring a "width" of a data set
- 8 Root-mean-square distance: Standard deviation
- 9 Correlated data
- 10 Rotating the axes
- 11 Rotating the data
- 12 Higher dimensions
- 13 What is the Singular-Value Decomposition (SVD)?
- 14 Rotations in 300 dimensions
