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mlmentorship

Book I · Chapter 1

Linear algebra and geometry

Start with linear maps, then study volume, spectra, decompositions, and derivatives.

Priority
Core
Difficulty
Foundation
Useful for
All ML roles
Interview rounds
Math, ML breadth

Chapter contents

6 entries · read in order
  1. 01
    Matrices as linear maps
    Concept
  2. 02
    Determinant and volume
    Concept
  3. 03
    Positive (semi-)definite matrices
    Concept
  4. 04
    Eigenvalues and the spectral theorem
    Concept
  5. 05
    SVD and PCA
    Concept
  6. 06
    Matrix calculus for ML
    Concept