We often think in binaries. something either happened or it did not. But a far better way to look at the world is through PROBABILISTIC THINKING. This is also how we should evaluate the most important decision in Mahendra Singh Dhoni s career. Listen in for the full d... Lees meer.

An introduction to the techniques and algorithms of the newest field in robotics. Probabilistic robotics is a new and growing area in robotics concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics probabilis... Lees meer.

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A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today s Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these developing methods that can... Lees meer.

Greatly expanded this new edition requires only an elementary background in discrete mathematics and offers a comprehensive introduction to the role of randomization and probabilistic techniques in modern computer science. Newly added chapters and sections cover topics... Lees meer.

A detailed and up-to-date introduction to machine learning presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning including deep learning through the unify... Lees meer.

Sarah Moss argues that in addition to full beliefs credences can constitute knowledge. She introduces the notion of probabilistic content and shows how it plays a central role not only in epistemology but in the philosophy of mind and language. Just you can believe an... Lees meer.

Probabilistic Deep Learning shows how probabilistic deep learning models gives readers the tools to identify and account for uncertainty and potential errors in their results. Starting by applying the underlying maximum likelihood principle of curve fitting to deep l... Lees meer.

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All of the sciences. physical biological and social. have a need for quantitative measurement. This influential series Foundations of Measurement established the formal foundations for measurement justifying the assignment of numbers to objects in terms of their st... Lees meer.

High-dimensional probability offers insight into the behavior of random vectors random matrices random subspaces and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability analysis and geometry it lends itself to applications in... Lees meer.

An integrated work in two volumes this text teaches readers to formulate analyze and evaluate Markov models. The first volume treats the basic process the second semi-Markov and decision processes. 1971 edition.... Lees meer.

In nonparametric and high-dimensional statistical models the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply and new foundations and ideas have been developed in the past several... Lees meer.

Three centuries ago Montmort and De Moivre published two of the first books on probability theory then called the doctrine of chances emphasizing its most important application at that time games of chance. This volume on the probabilistic aspects of gambling is a... Lees meer.

Account for uncertainties and optimize decision-making with this thorough exposition Decision theory is a body of thought and research seeking to apply a mathematical-logical framework to assessing probability and optimizing decision-making. It has developed robust too... Lees meer.