Bayesian Reasoning and Machine Learning – David Barber

Bayesian reasoning and machine learning are two powerful tools that have revolutionized the field of artificial intelligence. At the forefront of this advancement is David Barber, a well-known computer scientist and author whose work has greatly contributed to the development of these fields. David Barber is a Professor of Applied Mathematics and Professor of Computer
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Introduction to Reinforcement Learning – Marco Wiering and Martijn van Otterlo

Introduction to Reinforcement Learning – Marco Wiering and Martijn van Otterlo Reinforcement Learning (RL) is a powerful machine learning approach that has been gaining popularity in recent years due to its ability to learn and adapt to its environment without being explicitly programmed. This method has been successfully applied in diverse fields such as robotics,
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Astronomical Algorithms – Jean Meeus

Astronomical Algorithms – Jean Meeus Jean Meeus is a Belgian astronomer and author who has made significant contributions to the field of celestial mechanics. He is best known for his work on astronomical algorithms, which are mathematical formulas used to calculate the positions and movements of celestial objects such as planets, stars, and galaxies. Meeus
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Artificial Intelligence: A Modern Approach – Stuart Russell and Peter Norvig

Introduction Artificial intelligence (AI) has become one of the most talked-about and rapidly evolving fields in today’s digital era. It involves the development of computer systems that can perform tasks that usually require human intelligence, such as problem-solving, decision-making, and learning. Stuart Russell and Peter Norvig are two of the most influential figures in the
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Machine Learning: A Probabilistic Perspective – Kevin P. Murphy

Introduction Machine learning has become an increasingly popular field in recent years, and for good reason. It allows for computers to learn and improve from data without being explicitly programmed, making it a valuable tool in a variety of industries. However, many people are still unfamiliar with the underlying principles and theories behind machine learning.
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