Mathematics for Machine Learning uses concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines.

Best Machine Learning Book, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. With concrete examples, minimal theory, and two production-ready Python environments, author Aurelien Geron provides an intuitive understanding of concepts and tools for building intelligent systems.