Below is a curated list of English machine learning books that are widely recommended by experts in the field. These books cover a range of topics from the fundamentals of machine learning to advanced techniques and applications.
"Machine Learning: A Probabilistic Perspective" by Kevin P. Murphy This book offers a comprehensive introduction to machine learning that emphasizes the probabilistic approach. It is a great resource for understanding the underlying principles of machine learning algorithms.
"Pattern Recognition and Machine Learning" by Christopher M. Bishop A classic in the field, this book provides a solid foundation in pattern recognition and machine learning, with a focus on statistical methods.
"Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville This book is a deep dive into the theoretical and practical aspects of deep learning. It is an essential read for anyone interested in understanding the latest advancements in this area.
"Artificial Intelligence: A Modern Approach" by Russell and Norvig Although not exclusively focused on machine learning, this book is a foundational text in AI and provides a broad overview of the field, including machine learning.
"Reinforcement Learning: An Introduction" by Richard S. Sutton and Andrew G. Barto This book offers a clear and intuitive introduction to reinforcement learning, a branch of machine learning that focuses on decision-making through interaction with an environment.
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