Mathematics for Machine Learning by Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Requirements: .PDF reader, 16 mb
Overview: This self contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines.
For students and others with a mathematical background, these derivations provide a starting point to machine learning texts.
Genre: Non-Fiction > Educational