My notes when reading Mathematics for Machine Learning
- 2.Linear Algebra.pdf
- 3.Analytic Geometry.pdf
- 4.Matrix Decomposition.pdf
- 5.Vector Calculus.pdf
- 6.Probability and Distributions.pdf
- 7.Continuous Optimization.pdf
- 8.When Models Meets Data.pdf
- 9.Linear Regression.pdf
- 10.Dimentionality Reduction With Principal Component Analysis.pdf
- 11.Density Estimation With Gaussian Mixture Models
- 12.Classification With Support Vector Machines