Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal mo...(view full description)

Assuming some knowledge of calculus, this text offers numerous applied examples and exercises related to numerical methods. Written in a simple, direct, and unambiguous style, the book introduces students to a wide range of useful and important algorithms. Computer results are presented with full details so that the steps of the algorithm of each numerical method are visualized and interpreted....(view full description)

A guide that addresses basic descriptive statistics, reliability concepts, the exponential distribution, the Weibull distribution, reliability data plotting, systems models and reliability, and much more. It includes chapters on Bayesian reliability analysis, reliability metrics, and software reliability.

Designed to supplement the calculus course, provides a quick introduction to the basic ideas of linear algebra.

This text helps you succeed in finite mathematics and applied calculus by using clear explanations, real-life examples, and up-to-date technology. Real-life applications-such as satellite radio subscriptions, Google's revenue, job outsourcing, and the effects of smoking bans-are drawn from the areas of business and the behavioral, life, and social sciences. Portfolio profiles give you a firstha...(view full description)

Suitable for math students in general and calculus students in particular.