MACHINE LEARNING : A PROBABILISTIC PERSPECTIVE

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Published Date: 2024-06-27
Author Name: Pawan Kumar Gupt,a Piyush Gupta, Ashutosh Mohite, Akhilesh A. Waoo

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"Machine Learning: A Probabilistic Perspective" is a comprehensive guide that explores machine learning through the lens of probability theory. It covers a wide range of models and techniques, emphasizing the probabilistic principles that underpin these methods. The book balances theoretical foundations with practical applications, making it suitable for both academic and professional audiences. Key topics include Bayesian networks, graphical models, hidden Markov models, and various inference techniques, all presented with clarity and supported by numerous examples and exercises. This approach ensures that readers not only learn how to apply machine learning algorithms but also understand the probabilistic reasoning behind them.