The Probability Integral, Nahin

Автор: Chalmers, Dean
Название: Cambridge International AS & A Level Mathematics: Probability & Statistics 1 Coursebook
ISBN: 1108407307 ISBN-13(EAN): 9781108407304
Издательство: Cambridge Education
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Цена: 31150.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This series has been developed specifically for the Cambridge International AS & A Level Mathematics (9709) syllabus to be examined from 2020.

Автор: Brunton, Steven L. (university Of Washington) Kutz
Название: Data-driven science and engineering
ISBN: 1009098489 ISBN-13(EAN): 9781009098489
Издательство: Cambridge Academ
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Цена: 52790.00 T
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Описание: Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB (R), new chapters on reinforcement learning and physics-informed machine learning, and supplementary videos and code.

Автор: Bradley Efron , Trevor Hastie
Название: Computer Age Statistical Inference, Student Edition
ISBN: 1108823416 ISBN-13(EAN): 9781108823418
Издательство: Cambridge Academ
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Цена: 33790.00 T
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Описание: Computing power has revolutionized the theory and practice of statistical inference. Now in paperback, and fortified with 130 class-tested exercises, this book explains modern statistical thinking from classical theories to state-of-the-art prediction algorithms. Anyone who applies statistical methods to data will value this landmark text.

Автор: Senn, Stephen
Название: Dicing with death
ISBN: 1108999867 ISBN-13(EAN): 9781108999861
Издательство: Cambridge Academ
Рейтинг:
Цена: 21110.00 T
Наличие на складе: Заказано в издательстве.
Описание: From measles to malaria, from clinical trials to COVID and from life tables to the law, the second edition of Dicing with Death explains how the vital decisions we have to make both individually and collectively can be informed and improved by good data, statistical reasoning and analysis.

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: Haigh, John
Название: Probability: A Very Short Introduction
ISBN: 0199588481 ISBN-13(EAN): 9780199588480
Издательство: Oxford Academ
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Цена: 10550.00 T
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Описание: Making good decisions under conditions of uncertainty requires an appreciation of the way random chance works. In this Very Short Introduction, John Haigh provides a brief account of probability theory; explaining the philosophical approaches, discussing probability distributions, and looking its applications in science and economics.

Автор: E. T. Jaynes
Название: Probability Theory
ISBN: 0521592712 ISBN-13(EAN): 9780521592710
Издательство: Cambridge Academ
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Цена: 114050.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A comprehensive introduction to the role of probability theory in general scientific endeavour. This book provides an original interpretation of probability theory, showing the subject to be an extension of logic, and presenting new results and applications. Ideal for scientists working in any area involving inference from incomplete information.

Автор: Gallager
Название: Stochastic Processes
ISBN: 1107039754 ISBN-13(EAN): 9781107039759
Издательство: Cambridge Academ
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Цена: 74970.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world`s leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.

Автор: Glasserman
Название: Monte Carlo Methods in Financial Engineering
ISBN: 0387004513 ISBN-13(EAN): 9780387004518
Издательство: Springer
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Цена: 74530.00 T
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Описание: From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not."

Автор: Grimmett
Название: Probability and Random Processes 4ed
ISBN: 0198847599 ISBN-13(EAN): 9780198847595
Издательство: Oxford Academ
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Цена: 59130.00 T
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Описание: Probability is a core topic in science and life. This successful self-contained volume leads the reader from the foundations of probability theory and random processes to advanced topics and it presents a mathematical treatment with many applications to real-life situations.

Автор: Donald B. Percival, Andrew T. Walden
Название: Spectral Analysis for Univariate Time Series
ISBN: 1107028140 ISBN-13(EAN): 9781107028142
Издательство: Cambridge Academ
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Цена: 97150.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Spectral analysis is an important technique for interpreting time series data. This book uses the R language and real world examples to show data analysts interested in time series in the environmental, engineering and physical sciences how to bridge the gap between the statistical theory behind spectral analysis and its application to actual data.