Machine Learning: A Probabilistic Perspective

Machine Learning: A Probabilistic Perspective is a comprehensive guide to the principles of machine learning and probabilistic modeling. Murphy introduces readers to a wide range of machine learning techniques, covering topics like supervised learning, unsupervised learning, and reinforcement learning. The book provides detailed explanations of probabilistic models, graphical models, and Bayesian inference, helping readers understand the foundations of machine learning. By exploring a variety of machine learning algorithms and problem-solving strategies, the book equips readers with the knowledge to build and train machine learning models for a wide range of applications.