Maths for ML
Posts and notes about maths for ml.
Series & Posts
1
Why Maths Matters for ML: A Practical Overview
2 Scalars, Vectors, and Vector Spaces
3 Matrices and Matrix Operations
4 Matrix Inverses and Systems of Linear Equations
5 Eigenvalues and Eigenvectors
6 Matrix Decompositions: LU, QR, SVD
7 Norms, Distances, and Similarity
8 Calculus Review: Derivatives and the Chain Rule
9 Partial Derivatives and Gradients
10 The Jacobian and Hessian Matrices
11 Taylor series and local approximations
12 Probability fundamentals
13 Random variables and distributions
14 Bayes theorem and its role in ML
15 Information theory: entropy, KL divergence, cross-entropy