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Business Analytics, Bag


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Цена: 23734.00р.
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При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Bag
Название:  Business Analytics
ISBN: 9781138916111
Издательство: Taylor&Francis
Классификация:




ISBN-10: 1138916110
Обложка/Формат: Hardback
Страницы: 246
Вес: 0.50 кг.
Дата издания: 31.10.2016
Язык: English
Иллюстрации: 115 tables, black and white; 13 line drawings, black and white; 13 illustrations, black and white
Размер: 234 x 156 x 16
Читательская аудитория: Undergraduate
Ключевые слова: Business & management, BUSINESS & ECONOMICS / General,BUSINESS & ECONOMICS / Human Resources & Personnel Management,BUSINESS & ECONOMICS / Statistics
Основная тема: Business, Management and Accounting / Databases / Supplementary
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Европейский союз
Описание: This book provides a first-hand account of business analytics and its implementation, an account of the brief theoretical framework underpinning each component of business analytics, and gives a complete insightful understanding of developing and implementing analytical solution.


Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Автор: Kelleher John D., Macnamee Brian, D`Arcy Aoife
Название: Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies
ISBN: 0262029448 ISBN-13(EAN): 9780262029445
Издательство: MIT Press
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Цена: 13543.00 р.
Наличие на складе: Нет в наличии.

Описание:

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.

After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.

Data Mining and Business Analytics with R

Автор: Ledolter Johannes
Название: Data Mining and Business Analytics with R
ISBN: 111844714X ISBN-13(EAN): 9781118447147
Издательство: Wiley
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Цена: 17258.00 р.
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Описание: Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets.


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