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Learn · Linear Algebra for Machine Learning and Quantum Computing

Lecture 5 of 26Week 1

Least squares problems, reflections, rotations

Prof. Ranveer Singh · IIT Indore

Credits and licence

From
Linear Algebra for Machine Learning and Quantum Computing, IIT Indore (at NPTEL)
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
Who can watch
Tweens profiles and older. How courses are placed

All the lectures

  1. Matrix product as linear combinations YouTube
  2. Linear dependence and bases YouTube
  3. Inner products and projections YouTube
  4. Projection onto subspaces and projection matrices YouTube
  5. Least squares problems, reflections, rotations YouTube
  6. Gram-Schmidt orthogonalization and QR decomposition YouTube
  7. Four fundamental subspaces and their orthogonality YouTube
  8. Matrix rank and the rank-nullity theorem YouTube
  9. Gaussian elimination, pivots, and computing rank YouTube
  10. Matrix inverses and rank tests for linear systems YouTube
  11. Least-squares linear regression and normal equations YouTube
  12. Determinants, elimination, and invertibility YouTube
  13. Eigenvalues, eigenvectors, and the characteristic equation YouTube
  14. Diagonalization using eigenvectors, matrix powers, and long-term behavior YouTube
  15. Symmetric matrices, spectral theorem, and orthogonal diagonalization YouTube
  16. Positive definite matrices, quadratic forms, Cholesky decomposition, and optimization YouTube
  17. Singular value decomposition: singular values, singular vectors, construction, and rank YouTube
  18. Principal component analysis: variance, covariance, projection, and dimensionality reduction YouTube
  19. PCA through SVD, low-rank approximation, image compression, and Eckart–Young theorem YouTube
  20. Random walks, Markov chains, stationary distributions, spectral mixing, and Monte Carlo simulation YouTube
  21. Clustering, K-Means, and Introduction to Spectral Clustering YouTube
  22. Mathematical Reasoning for Spectral Clustering YouTube
  23. Complex Linear Algebra, Qubits, and Measurement YouTube
  24. Single-Qubit Gates: Actions and Examples YouTube
  25. Multi-Qubit States, Gates, and Density Matrices YouTube
  26. Separable States and Entanglement YouTube