An Introduction to IoT Analytics, Perros, Harry G.

Автор: Joseph K. Blitzstein, Jessica Hwang
Название: Introduction to Probability, Second Edition
ISBN: 1138369918 ISBN-13(EAN): 9781138369917
Издательство: Taylor&Francis
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Цена: 11176.00 р.
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Описание: Assumes one-semester of calculus. "Stories" make distributions (Normal, Binomial, Poisson that are widely-used in statistics) easier to remember, understand. Many books write down formulas without explaining clearly why these particular distributions are important or how they are all connected.

Автор: Miroslav Kubat
Название: An Introduction to Machine Learning
ISBN: 3319348868 ISBN-13(EAN): 9783319348865
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications.

Автор: Boyd Stephen
Название: Introduction to Applied Linear Algebra
ISBN: 1316518965 ISBN-13(EAN): 9781316518960
Издательство: Cambridge Academ
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Цена: 6811.00 р.
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Описание: A groundbreaking introductory textbook covering the linear algebra methods needed for data science and engineering applications. It combines straightforward explanations with numerous practical examples and exercises from data science, machine learning and artificial intelligence, signal and image processing, navigation, control, and finance.

Автор: Chung K. L., AitSahlia Farid
Название: Elementary Probability Theory / With Stochastic Processes and an Introduction to Mathematical Finance
ISBN: 038795578X ISBN-13(EAN): 9780387955780
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Provides an introduction to probability theory and its applications.

Автор: David Alciatore and Michael B Histand
Название: Introduction to Mechatronics and Measurement Systems
ISBN: 0071086048 ISBN-13(EAN): 9780071086042
Издательство: McGraw-Hill
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Цена: 8275.00 р.
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Описание: Provides comprehensive coverage of the field of mechatronics for mechanical, electrical and aerospace engineering majors. This title presents a review of electrical circuits, solid-state devices, digital circuits, and motors - which are fundamental to understanding mechatronic systems.

Автор: Perros Harry G.
Название: An Introduction to Iot Analytics
ISBN: 0367687828 ISBN-13(EAN): 9780367687823
Издательство: Taylor&Francis
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Цена: 18374.00 р.
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Описание: This book covers techniques that can be used to analyze data from IoT sensors and also addresses questions regarding the performance of an IoT system. It strikes a balance between practice and theory so that one can learn how to apply these tools in practice with a good understanding of their inner workings.

Автор: Efron
Название: An Introduction to the Bootstrap
ISBN: 0412042312 ISBN-13(EAN): 9780412042317
Издательство: Taylor&Francis
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Цена: 22968.00 р.
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Описание: An exploration of the many different bootstrap techniques. It discusses useful statistical techniques through real data examples and covers nonparametric regression, density estimation, classification trees, and least median squares regression. There are numerous exercises.

Автор: MacInnes John
Название: An Introduction to Secondary Data Analysis with IBM SPSS Statis
ISBN: 1446285774 ISBN-13(EAN): 9781446285770
Издательство: Sage Publications
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Цена: 6968.00 р.
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Описание: John MacInnes takes the fear out of statistics for students, and helps to raise the standards of their quantitative methods skills, by clearly and accessibly introducing all that`s needed to know about using secondary data and working with IBM SPSS Statistics.

Автор: Oliver Kramer
Название: A Brief Introduction to Continuous Evolutionary Optimization
ISBN: 3319034219 ISBN-13(EAN): 9783319034218
Издательство: Springer
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Цена: 9141.00 р.
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Описание: This book introduces heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. It presents heuristic extensions that allow optimization in constrained, multimodal and multi-objective solution spaces.

Автор: Ball, Rafael
Название: An Introduction to bibliometrics
ISBN: 008102150X ISBN-13(EAN): 9780081021507
Издательство: Elsevier Science
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Цена: 10603.00 р.
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Описание:

An Introduction to Bibliometrics: New Development and Trends provides a comprehensible, readable and easy to read introduction to bibliometrics. Importantly, the book surveys the latest developments of bibliometrics (such as altmetrics, etc.) and how the field is likely to change over the next decade. In the literature, bibliometrics is generally discussed from one of two perspectives: (1) Purely mathematical/statistical or (2) Its sociological implications. Both approaches are very far from how most users want to apply bibliometrics. This book fills that need by providing tactics on how bibliometrics can be applied to their sphere of scientific activity.

Автор: Dorman, Michael,
Название: Introduction to web mapping /
ISBN: 0367861186 ISBN-13(EAN): 9780367861186
Издательство: Taylor&Francis
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Цена: 9645.00 р.
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Описание: A web map is an interactive display of geographic information, in the form of a web page, that you can use to tell stories and answer questions. Introduction to Web Mapping teaches you how to develop online interactive web maps and web mapping applications, using standard web technologies: HTML, CSS and JavaScript.

Автор: John Fox
Название: Regression Diagnostics: An Introduction
ISBN: 1544375220 ISBN-13(EAN): 9781544375229
Издательство: Sage Publications
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Цена: 5859.00 р.
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Описание:

Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted? Regression diagnostics not only reveal deficiencies in a regression model that has been fit to data but in many instances may suggest how the model can be improved. The Second Edition of this bestselling volume by John Fox considers two important classes of regression models: the normal linear regression model (LM), in which the response variable is quantitative and assumed to have a normal distribution conditional on the values of the explanatory variables; and generalized linear models (GLMs) in which the conditional distribution of the response variable is a member of an exponential family. R code and data sets for examples within the text can be found on an accompanying website at https://tinyurl.com/RegDiag.