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Textual Data Science with R, Becue-Bertaut, Monica


Варианты приобретения
Цена: 7501.00р.
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Наличие: Поставка под заказ.  Есть в наличии на складе поставщика.
Склад Америка: Есть  
При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Becue-Bertaut, Monica
Название:  Textual Data Science with R
ISBN: 9781032093659
Издательство: Taylor&Francis
Классификация:




ISBN-10: 103209365X
Обложка/Формат: Paperback
Страницы: 212
Вес: 0.31 кг.
Дата издания: 30.06.2021
Серия: Chapman & hall/crc computer science & data analysis
Язык: English
Иллюстрации: 50 illustrations, black and white
Размер: 234 x 156
Читательская аудитория: Tertiary education (us: college)
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Поставляется из: Европейский союз
Описание: Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming es


The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10480.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Excel data analysis

Автор: Guerrero, Hector
Название: Excel data analysis
ISBN: 3030012786 ISBN-13(EAN): 9783030012786
Издательство: Springer
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Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book offers a comprehensive and readable introduction to modern business and data analytics.

Scientific Data Analysis

Автор: Currell Graham
Название: Scientific Data Analysis
ISBN: 0198712545 ISBN-13(EAN): 9780198712541
Издательство: Oxford Academ
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Цена: 7602.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Drawing on the author`s extensive experience of supporting students undertaking projects, Scientific Data Analysis is a guide for any science undergraduate or beginning graduate who needs to analyse their own data, and wants a clear, step-by-step description of how to carry out their analysis in a robust, error-free way.

Data science

Автор: Timbers, Tiffany-anne (university Of British Colum
Название: Data science
ISBN: 0367524686 ISBN-13(EAN): 9780367524685
Издательство: Taylor&Francis
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Цена: 7501.00 р.
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Описание: Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and cleaning, create effective visualizations, and extract insights from data using supervised predictive models.

Satellite Remote Sensing in Hydrological Data Assimilation

Автор: Mehdi Khaki
Название: Satellite Remote Sensing in Hydrological Data Assimilation
ISBN: 3030373746 ISBN-13(EAN): 9783030373740
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book presents the fundamentals of data assimilation and reviews the application of satellite remote sensing in hydrological data assimilation. Satellite remote sensing data provides a great opportunity to improve the performance of models through data assimilation.

Data Science for Mathematicians

Автор: Nathan Carter
Название: Data Science for Mathematicians
ISBN: 0367027054 ISBN-13(EAN): 9780367027056
Издательство: Taylor&Francis
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Цена: 24499.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Mathematicians have skills that would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. This handbook will assist mathematicians to better understand the opportunities presented by data science.

An Introduction to IoT Analytics

Автор: Perros, Harry G.
Название: An Introduction to IoT Analytics
ISBN: 0367686317 ISBN-13(EAN): 9780367686314
Издательство: Taylor&Francis
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Цена: 7348.00 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.

Foundations of statistics for data scientists :

Автор: Agresti, Alan,
Название: Foundations of statistics for data scientists :
ISBN: 0367748452 ISBN-13(EAN): 9780367748456
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание: This book shows the elements of statistical science that are highly relevant for students who plan to become data scientists. However, most of the content focuses on the statistical methods and the theory behind them, rather than on data science.

Econometric Analysis of Panel Data

Автор: Baltagi Badi H.
Название: Econometric Analysis of Panel Data
ISBN: 3030539520 ISBN-13(EAN): 9783030539528
Издательство: Springer
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Цена: 9083.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Introduction.- The One-Way Error Component Regression Model.- The Two-Way Error Component Regression Model.- Test of Hypotheses with Panel Data.- Heteroskedasticity and Serial Correlation in the Error Component Model.- Seemingly Unrelated Regressions with Error Components.- Simultaneous Equations with Error Components.- Dynamic Panel Data Models.- Unbalanced Panel Data Models.- Special Topics.- Limited Dependent Variables and Panel Data.- Nonstationary Panels.- Spatial Panel Data Models.

Data science and innovations for intelligent systems :

Автор: Kavita Taneja, Harmunish Taneja
Название: Data science and innovations for intelligent systems :
ISBN: 0367676273 ISBN-13(EAN): 9780367676278
Издательство: Taylor&Francis
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Цена: 22202.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book not only focuses on the practical applications of data science to achieve computational excellence, but also digs deep into the issues and implications of intelligent systems.

Modern Statistical Methods for Spatial and Multivariate Data

Автор: Norou Diawara
Название: Modern Statistical Methods for Spatial and Multivariate Data
ISBN: 3030114309 ISBN-13(EAN): 9783030114305
Издательство: Springer
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Цена: 11878.00 р.
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Описание:

This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques.
Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
Handbook of Statistical Analysis and Data Mining Applications, 2 ed.

Автор: Robert Nisbet , Gary Miner, Ken Yale
Название: Handbook of Statistical Analysis and Data Mining Applications, 2 ed.
ISBN: 0124166326 ISBN-13(EAN): 9780124166325
Издательство: Elsevier Science
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Цена: 13304.00 р.
Наличие на складе: Поставка под заказ.

Описание:

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application.

This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas--from science and engineering, to medicine, academia and commerce.

  • Includes input by practitioners for practitioners
  • Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models
  • Contains practical advice from successful real-world implementations
  • Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions
  • Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

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