Learn IT - Books tags probability

From Gestalt Theory to Image Analysis: A Probabilistic Approach (Interdisciplinary Applied Mathematics)

Springer, 2007

The theory in these notes was taught between 2002 and 2005 at the graduate schools of Ecole Normale Sup´erieure de Cachan, Ecole Polytechnique de Palaiseau, Universitat Pompeu Fabra, Barcelona, Universitat de les Illes of Balears, Palma, and University of California at Los Angeles. It is also being taught by Andr`es Almansa...

Fundamentals of Probability and Statistics for Engineers

John Wiley & Sons, 2004

Many books are already available on the general topic of 'probability and statistics for engineers and scientists', so why choose this one? This textbook differs in that it has been prepared very much with students and their needs in mind. Having been classroom tested over many years, it is a true "learner's book" made for students who...

Game Theory: Decisions, Interaction and Evolution (Springer Undergraduate Mathematics Series)

Springer, 2006

This book is an introduction to game theory from a mathematical perspective. It is intended to be a first course for undergraduate students of mathematics, but I also hope that it will contain something of interest to advanced students or researchers in biology and economics who often encounter the basics of game theory informally via relevant...

Real Analysis and Probability (Cambridge Studies in Advanced Mathematics)

Cambridge University Press, 2002

This classic textbook, now reissued, offers a clear exposition of modern probability theory and of the interplay between the properties of metric spaces and probability measures. The new edition has been made even more self-contained than before; it now includes a foundation of the real number system and the Stone-Weierstrass theorem on...

Basic Concepts in Computational Physics

Springer, 2013

With the development of ever more powerful computers a new branch of physics and engineering evolved over the last few decades: Computer Simulation or Computational Physics. It serves two main purposes:

- Solution of complex mathematical problems such as, differential equations, minimization/optimization, or high-dimensional...

Computational Probability: Algorithms and Applications in the Mathematical Sciences (International Series in Operations Research & Management Science)

Springer, 2007

This title organizes computational probability methods into a systematic treatment. The book examines two categories of problems. "Algorithms for Continuous Random Variables" covers data structures and algorithms, transformations of random variables, and products of independent random variables. "Algorithms for...

When Least Is Best: How Mathematicians Discovered Many Clever Ways to Make Things as Small (or as Large) as Possible

Princeton Press, 2007

This book was terrific fun to read! I thought I would skim the chapters to write my review, but I was hooked by the preface, and read through the first 100 pages in one sitting... [Nahin shows] obvious delight and enjoyment--he is having fun and it is contagious. -- Bonnie Shulman MAA Online When Least is Best is clearly the result of immense...

The Unfinished Game: Pascal, Fermat, and the Seventeenth-Century Letter that Made the World Modern

Basic Books, 2008

PublishersWeekly.com

“This informative book is a lively, quick read for anyone who wonders about the science of predicting what’s next and how deeply it affects our lives.”

New Scientist
“This breezy book shows why probability theory, though...

Learning Bayesian Models with R

Packt Publishing, 2015

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems

About This Book

Understand the principles of Bayesian Inference with less mathematical equations

Learn state-of-the art Machine Learning methods

Familiarize...

Mathematics of Uncertainty: Ideas, Methods, Application Problems

Springer, 2005

"Mathematics of Uncertainty" provides the basic ideas and foundations of uncertainty, covering the fields of mathematics in which uncertainty, variability, imprecision and fuzziness of data are of importance. This introductory book describes the basic ideas of the mathematical fields of uncertainty from simple interpolation to...

Credit Portfolio Management

John Wiley & Sons, 2003

Market realities have forced many financial institutions (and will force many others in the future) to change the way they manage their portfolios of credit assets. Evidence of this change can be seen in the rapid growth of secondary loan trading, credit derivatives, and loan securitizations. Less obvious–but far more important–is the...

Machine Learning and Data Mining

Woodhead Publishing, 2007

The book describes the basics of machine learning principles and algorithms that are used in data mining and is intended for students of computer science, researchers who need to adapt various algorithms for particular data mining tasks, and for education of sophisticated users of machine learning and data mining tools.

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