Machine Learning from Scratch (Book)
Machine Learning from Scratch is a book that covers the building blocks of the most common methods in machine learning. It covers the concepts, construction, and implementations of Ordinary Linear Regression, Linear Regression Extensions, Discriminative Classifiers, Generative Classifiers, Decision Trees, Tree Ensemble Methods, and Neural Networks. The book was written for readers interested in seeing machine learning algorithms derived from start to finish. It does not review best practices or discuss in depth when certain models are more appropriate than others.