Mathematics for Machine Learning
Foundation in linear algebra, calculus, probability, and optimization essential for understanding ML.
About the book
Essential mathematical foundations for ML covering linear algebra, geometry, calculus, probability, and optimization. Derives four central ML methods: linear regression, PCA, GMMs, and SVMs from mathematical first principles.
Summary
Summary coming soon!