The book "Probability for Statistics and Machine Learning" covers classic and modern probability theory, statistical topics, and machine learning tools. It is written in an easy-to-understand style with many examples and exercises. The book is suitable for graduate courses or self-study in statistics, computer science, or mathematics. It includes detailed discussions on distribution theory, simulation, Markov chains, Gaussian processes, and more. The book is a valuable resource for understanding probability and its applications in various fields.