Описание: This book constitutes revised selected papers from the Second International Workshop on Future and Emerging Trends in Language Technology, FETLT 2016, which took place in Seville, Spain, in November 2016. The 10 full papers and 5 position papers presented in this volume were carefully reviewed and selected from 18 submissions.
Автор: Sourav Mazumder; Robin Singh Bhadoria; Ganesh Chan Название: Distributed Computing in Big Data Analytics ISBN: 3319598333 ISBN-13(EAN): 9783319598338 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use.This book fills the literature gap by addressing key aspects of distributed processing in big data analytics.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
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.
Автор: Min Chen; Shiwen Mao; Yin Zhang; Victor C.M. Leung Название: Big Data ISBN: 3319062441 ISBN-13(EAN): 9783319062440 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This Springer Brief provides a comprehensive overview of the background and recent developments of big data. The value chain of big data is divided into four phases: data generation, data acquisition, data storage and data analysis.
Автор: Robert Qiu; Michael Wicks Название: Cognitive Networked Sensing and Big Data ISBN: 1489997261 ISBN-13(EAN): 9781489997265 Издательство: Springer Рейтинг: Цена: 19589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the challenges that are unique to this area such as synchronization caused by the high mobility of the nodes. It discusses the integration of software defined radio implementation and testbed development.
Описание: This book presents machine learning models and algorithms to address big data classification problems. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The third part presents the topics required to understand and select machine learning techniques to classify big data.
Автор: Shaoxu Song; Matthias Renz; Yang-Sae Moon Название: Web and Big Data ISBN: 3319697803 ISBN-13(EAN): 9783319697802 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed post-conference proceedings of the First APWeb-WAIM 2017 Workshops, held jointly with the First International Joint Conference APWeb-WAIM 2017, held in Beijing, China, in July 2017.
Автор: Pethuru Raj; Anupama Raman; Dhivya Nagaraj; Siddha Название: High-Performance Big-Data Analytics ISBN: 3319207431 ISBN-13(EAN): 9783319207438 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data;
Автор: Weizhong Qiang; Xianghan Zheng; Ching-Hsien Hsu Название: Cloud Computing and Big Data ISBN: 3319284290 ISBN-13(EAN): 9783319284293 Издательство: Springer Рейтинг: Цена: 7826.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of theSecond International Conference on Cloud Computing and Big Data, CloudCom-Asia2015, held in Huangshan, China, in June 2015. The 29 full papers and two keynote speeches werecarefully reviewed and selected from 106 submissions.
Автор: Jianfeng Zhan; Rui Han; Roberto V. Zicari Название: Big Data Benchmarks, Performance Optimization, and Emerging Hardware ISBN: 3319290053 ISBN-13(EAN): 9783319290058 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Benchmarking.- Benchmarking and Workload Characterization.- Performance Optimization and Evaluation.- Emerging Hardware.
Автор: Pethuru Raj; Anupama Raman; Dhivya Nagaraj; Siddha Название: High-Performance Big-Data Analytics ISBN: 3319363247 ISBN-13(EAN): 9783319363240 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data;
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