Probability Foundations for Engineers, Nachlas, Joel A. (Virginia Polytechnic Institute and State University, Department of Industrial & Systems Engineering, Blacksburg, USA)

Автор: Nachlas, Joel A.
Название: Probability Foundations for Engineers
ISBN: 1466502991 ISBN-13(EAN): 9781466502994
Издательство: Taylor&Francis
Цена: 153120 T
Наличие на складе: Нет в наличии.

Автор: Thomas A. Garrity
Название: All the Math You Missed
ISBN: 1009009192 ISBN-13(EAN): 9781009009195
Издательство: Cambridge Academ
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Цена: 26400.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The second edition of this bestselling book provides an overview of the key topics in undergraduate mathematics, allowing beginning graduate students to fill in any gaps in their knowledge. With numerous examples, exercises and suggestions for further reading, it is a must-have for anyone looking to learn some serious mathematics quickly.

Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Название: Mathematics for Machine Learning
ISBN: 110845514X ISBN-13(EAN): 9781108455145
Издательство: Cambridge Academ
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Цена: 42230.00 T
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Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

Автор: Crane
Название: Probabilistic Foundations of Statistical Network Analysis
ISBN: 1138585998 ISBN-13(EAN): 9781138585997
Издательство: Taylor&Francis
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Цена: 132710.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power law, all of which play a central role in contemporary data science and machine learning applications. The book rewards readers with a clear and intuitive understanding of the subtle interplay between basic principles of statistical inference, empirical properties of network data, and technical concepts from probability theory. Its mathematically rigorous, yet non-technical, exposition makes the book accessible to professional data scientists, statisticians, and computer scientists as well as practitioners and researchers in substantive fields. Newcomers and non-quantitative researchers will find its conceptual approach invaluable for developing intuition about technical ideas from statistics and probability, while experts and graduate students will find the book a handy reference for a wide range of new topics, including edge exchangeability, relative exchangeability, graphon and graphex models, and graph-valued Levy process and rewiring models for dynamic networks. The author’s incisive commentary supplements these core concepts, challenging the reader to push beyond the current limitations of this emerging discipline. With an approachable exposition and more than 50 open research problems and exercises with solutions, this book is ideal for advanced undergraduate and graduate students interested in modern network analysis, data science, machine learning, and statistics. Harry Crane is Associate Professor and Co-Director of the Graduate Program in Statistics and Biostatistics and an Associate Member of the Graduate Faculty in Philosophy at Rutgers University. Professor Crane’s research interests cover a range of mathematical and applied topics in network science, probability theory, statistical inference, and mathematical logic. In addition to his technical work on edge and relational exchangeability, relative exchangeability, and graph-valued Markov processes, Prof. Crane’s methods have been applied to domain-specific cybersecurity and counterterrorism problems at the Foreign Policy Research Institute and RAND’s Project AIR FORCE. ? ? ? ? ? ?

Автор: Bollman
Название: Mathematics of Keno and Lotteries
ISBN: 1138723800 ISBN-13(EAN): 9781138723801
Издательство: Taylor&Francis
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Цена: 158230.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Mathematics of Keno and Lotteries is an elementary treatment of the mathematics, primarily probability and simple combinatorics, involved in lotteries and keno. Keno has a long history as a high-advantage, high-payoff casino game, and state lottery games such as Powerball are mathematically similar.

Автор: Gross, Benedict H.,
Название: Fat chance :
ISBN: 1108728189 ISBN-13(EAN): 9781108728188
Издательство: Cambridge Academ
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Цена: 25350.00 T
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Описание: Designed for the intellectually curious, this book provides a solid foundation in basic probability theory in a charming style, without technical jargon. This text will immerse the reader in a mathematical view of the world, and teach them techniques to solve real-world problems both inside and outside the casino.

Автор: Ross, Sheldon M.
Название: Introduction To Probability And Statistics For Engineers And Scientists
ISBN: 0128243465 ISBN-13(EAN): 9780128243466
Издательство: Elsevier Science
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Цена: 110030.00 T
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Описание: Letter Jam is a 2-6 player cooperative word game where players assist each other in composing meaningful words from letters around the table. The trick is holding the letter card so that it`s only visible to other players and not to you.At the start of the game, each player receives a set of face-down letter cards that can be arranged to form an existing word. The setup can be prepared by using a special card scanning app, or by players selecting words for each other. Each player then puts their first card in their stand facing the other players without looking at it, and the game begins.The game is played in turns. Each turn, players simultaneously search other players` letters to see what words they can spell out (telling the others the length of the word they can make up). The player who offers the longest word can then be chosen as the clue giver.The clue giver spells out their clue by putting numbered tokens in front of the other players. Number one goes to the player whose letter comes first in the clue, number two to the second letter etc. They can always use a wild card which can be any letter, but they cannot tell others which letter it represents.Each player with a numbered token (or tokens) in front of them then tries to figure out what their letter is. If they do, they place the card face down before revealing the next letter. At the end of the game, players can then rearrange the cards to try to form an existing word. All players then reveal their cards to see if they were successful or not. The more players who have an existing word in front of them, the bigger their common success.

Автор: Charles A. Bouman
Название: Foundations of Computational Imaging: A Model-Based Approach
ISBN: 1611977126 ISBN-13(EAN): 9781611977127
Издательство: Mare Nostrum (Eurospan)
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Цена: 70230.00 T
Наличие на складе: Нет в наличии.
Описание: Collecting a set of classical and emerging methods that otherwise would not be available in a single treatment, Foundations of Computational Imaging: A Model-Based Approach is the first book to define a common foundation for the mathematical and statistical methods used in computational imaging. The book is designed to bring together an eclectic group of researchers with a wide variety of applications and disciplines including applied math, physics, chemistry, optics, and signal processing, to address a collection of problems that can benefit from a common set of methods. Inside, readers will find:Basic techniques of model-based image processing.A comprehensive treatment of Bayesian and regularized image reconstruction methods.An integrated treatment of advanced reconstruction techniques such as majorization, constrained optimization, ADMM, and Plug-and-Play methods for model integration.Foundations of Computational Imaging can be used in courses on Model-Based or Computational Imaging, Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. It is also for researchers or practitioners in medical imaging, scientific imaging, commercial imaging, or industrial imaging.

Автор: Morrison, Faith A.
Название: Uncertainty analysis for engineers and scientists
ISBN: 1108745741 ISBN-13(EAN): 9781108745741
Издательство: Cambridge Academ
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Цена: 46470.00 T
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Описание: Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Whether you are new to the sciences or an experienced engineer, this useful text provides a practical approach to performing error analysis.

Автор: Alan Agresti
Название: Foundations of Linear and Generalized Linear Models
ISBN: 1118730038 ISBN-13(EAN): 9781118730034
Издательство: Wiley
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Цена: 111880.00 T
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Описание: A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models.

Автор: Gin?
Название: Mathematical Foundations of Infinite-Dimensional Statistical Models
ISBN: 1107043166 ISBN-13(EAN): 9781107043169
Издательство: Cambridge Academ
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Цена: 99270.00 T
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Описание: High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus on function estimation problems arising from random samples (density estimation) or from Gaussian regression/signal in white noise problems.

Название: Stochastic Simulation and Monte Carlo Methods
ISBN: 3642393624 ISBN-13(EAN): 9783642393624
Издательство: Springer
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Цена: 55890.00 T
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Описание: The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes.

Автор: Salsburg
Название: Errors, Blunders And Lies
ISBN: 1498795781 ISBN-13(EAN): 9781498795784
Издательство: Taylor&Francis
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Цена: 30610.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this follow-up to the author`s bestselling classic, "The Lady Tasting Tea," David Salsburg takes a fresh and insightful look at the history of statistical development by examing errors, blunders and outright lies in many different models taken from a variety of fields including economics, biology, physics and sports.