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Multimedia data mining and analytics, 


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Цена: 16769.00р.
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Название:  Multimedia data mining and analytics
ISBN: 9783319149974
Издательство: Springer
Классификация:




ISBN-10: 3319149970
Обложка/Формат: Hardcover
Страницы: 454
Вес: 0.86 кг.
Дата издания: 01.04.2015
Язык: English
Иллюстрации: 48 tables, black and white; 153 illustrations, color; 35 illustrations, black and white; xiv, 454 p. 188 illus., 153 illus. in color.
Размер: 247 x 165 x 25
Читательская аудитория: Professional & vocational
Подзаголовок: Disruptive innovation
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Multimedia Data Mining and Analytics


Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking

Автор: Foster Provost
Название: Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking
ISBN: 1449361323 ISBN-13(EAN): 9781449361327
Издательство: Wiley
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Цена: 6334.00 р.
Наличие на складе: Есть (1 шт.)
Описание: This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.

Data Mining: The Textbook

Автор: С.Aggarwal
Название: Data Mining: The Textbook
ISBN: 3319141414 ISBN-13(EAN): 9783319141411
Издательство: Springer
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Цена: 9781.00 р.
Наличие на складе: Поставка под заказ.

Описание: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.

Multimedia Data Mining and Knowledge Discovery

Автор: Valery A. Petrushin; Latifur Khan
Название: Multimedia Data Mining and Knowledge Discovery
ISBN: 1447160134 ISBN-13(EAN): 9781447160137
Издательство: Springer
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Цена: 21661.00 р.
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Описание: This volume provides an overview of multimedia data mining and knowledge discovery and discusses the variety of hot topics in multimedia data mining research. It describes the objectives and current tendencies in multimedia data mining research and their applications.

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.

Data Mining and Predictive Analytics

Автор: Larose Daniel T
Название: Data Mining and Predictive Analytics
ISBN: 1118116194 ISBN-13(EAN): 9781118116197
Издательство: Wiley
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Цена: 18842.00 р.
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Описание: Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis.

Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery

Автор: Walter W. Piegorsch
Название: Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery
ISBN: 111903065X ISBN-13(EAN): 9781119030652
Издательство: Wiley
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Цена: 2685.00 р.
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Описание: Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery.

Handbook of Data Mining and Learning Analytics

Автор: ElAtia Samira
Название: Handbook of Data Mining and Learning Analytics
ISBN: 1118998235 ISBN-13(EAN): 9781118998236
Издательство: Wiley
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Цена: 17258.00 р.
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Описание: Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates.

Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner

Автор: Galit Shmueli, Peter C. Bruce, Nitin R. Patel
Название: Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner
ISBN: 1118729277 ISBN-13(EAN): 9781118729274
Издательство: Wiley
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Цена: 17741.00 р.
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Описание: Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.

Social Media Data Mining and Analytics

Автор: Szabo Gabor, Boykin Oscar
Название: Social Media Data Mining and Analytics
ISBN: 1118824857 ISBN-13(EAN): 9781118824856
Издательство: Wiley
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Цена: 5542.00 р.
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Описание: Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Written by Dr.

Intelligent Data Mining in Law Enforcement Analytics

Автор: Paolo Massimo Buscema; William J. Tastle
Название: Intelligent Data Mining in Law Enforcement Analytics
ISBN: 9400796013 ISBN-13(EAN): 9789400796010
Издательство: Springer
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Цена: 29209.00 р.
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Описание: In this thorough review of cutting-edge methods in law-enforcement data mining, the authors bring the latest research on artificial intelligence to life with chapters on key neural network developments in law enforcement that make criminality more foreseeable.

Data Mining: Concepts and Techniques,

Автор: Jiawei Han
Название: Data Mining: Concepts and Techniques,
ISBN: 0123814790 ISBN-13(EAN): 9780123814791
Издательство: Elsevier Science
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Цена: 9720.00 р.
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Описание: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.

Big Data Analytics for Sensor-Network Collected Intelligence

Автор: Hsu, Hui-Huang
Название: Big Data Analytics for Sensor-Network Collected Intelligence
ISBN: 0128093935 ISBN-13(EAN): 9780128093931
Издательство: Elsevier Science
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Цена: 15159.00 р.
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Описание:

Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services.

It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality.

In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation.

Indexing: The books of this series are submitted to EI-Compendex and SCOPUS


  • Contains contributions from noted scholars in computer science and electrical engineering from around the globe
  • Provides a broad overview of recent developments in sensor collected intelligence
  • Edited by a team comprised of leading thinkers in big data analytics

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