Bayesian Machine Learning in Quantitative Finance: Theory and Practical Applications
by Wilson Tsakane Mongwe, Rendani Mbuvha, Tshilidzi Marwala
Bayesian Machine Learning in Quantitative Finance: Theory and Practical Applications presents an integrated treatment of Bayesian methods and machine learning within quantitative finance. Combining theory with practical applications, it offers readers a foundation for understanding computational and probabilistic approaches to financial analysis and related decision-making.
About This Book
Bayesian Machine Learning in Quantitative Finance: Theory and Practical Applications examines the relationship between Bayesian methods, machine learning, and quantitative finance.
The book brings together theoretical concepts and practical applications, offering a framework for understanding how these approaches can be used in financial analysis.
It is suited to readers seeking an integrated view of probabilistic modeling, machine learning, and quantitative financial practice.
Written by Wilson Tsakane Mongwe, Rendani Mbuvha, and Tshilidzi Marwala, the book focuses on the intersection of modern computational methods and finance.
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