Описание: This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business.
Автор: Jeng-Shyang Pan; Vaclav Snasel; Emilio S. Corchado Название: Intelligent Data analysis and its Applications, Volume II ISBN: 3319077724 ISBN-13(EAN): 9783319077727 Издательство: Springer Рейтинг: Цена: 32142.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents the proceedings of the First Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2014), which was hosted by Shenzhen Graduate School of Harbin Institute of Technology and was held in Shenzhen City on June 13-15, 2014.
Автор: Jeng-Shyang Pan; Vaclav Snasel; Emilio S. Corchado Название: Intelligent Data analysis and its Applications, Volume I ISBN: 3319077759 ISBN-13(EAN): 9783319077758 Издательство: Springer Рейтинг: Цена: 32142.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents the proceedings of the First Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2014), which was hosted by Shenzhen Graduate School of Harbin Institute of Technology and was held in Shenzhen City on June 13-15, 2014.
Автор: Zhang, Jianye Zhang, Peng Название: Time series analysis methods and applications for flight data ISBN: 3662534282 ISBN-13(EAN): 9783662534281 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: As mass flight data possesses the typical characteristics of time series, the time series analysis methods and their application for flight data have been illustrated from several aspects, such as data filtering, data extension, feature optimization, similarity search, trend monitoring, fault diagnosis, and parameter prediction, etc.
Описание: This book highlights recent advances in intelligent data analysis, computational intelligence, signal processing, and all associated applications of artificial intelligence. It gathers papers presented at the ECC 2017, the Fourth Euro-China Conference on Intelligent Data Analysis and Applications. The aim of the ECC was to provide an internationally respected forum for scientific research in the broad areas of intelligent data analysis, computational intelligence, signal processing, and all associated applications of artificial intelligence (AI). The fourth installment of the ECC was jointly organized by the University of M?laga, Spain; the V?B - Technical University of Ostrava, Czech Republic; and Fujian University of Technology, Fuzhou, China. The conference took place in M?laga, Spain on October 9–11, 2017.
Автор: Francesco Mola; Claudio Conversano; Maurizio Vichi Название: Classification, (Big) Data Analysis and Statistical Learning ISBN: 3319557076 ISBN-13(EAN): 9783319557076 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pula (Cagliari), Italy, October 8–10, 2015.
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
Автор: Mirjana Ivanovi?; Lakhmi C. Jain Название: E-Learning Paradigms and Applications ISBN: 364241964X ISBN-13(EAN): 9783642419645 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the state-of-the-art of e-learning and tutoring systems, and discusses their capabilities and benefits that stem from integrating software agents. It includes various case studies to validate the usefulness of the presented paradigms.
Автор: Thanasis Daradoumis; Santi Caball?; Joan Manuel Ma Название: Intelligent Collaborative e-Learning Systems and Applications ISBN: 3642040004 ISBN-13(EAN): 9783642040009 Издательство: Springer Рейтинг: Цена: 22203.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Focusing on what has become a major research theme in the CSCL and CSCW research community, the authors provide new insights, fresh results and imaginative approaches both on the analysis and the development of more powerful e-collaboration settings.
Автор: Alejandro Pe?a-Ayala Название: Learning Analytics: Fundaments, Applications, and Trends ISBN: 3319529765 ISBN-13(EAN): 9783319529769 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Learning Analytics in Higher Education.- A Literature Review.- Teaching and Learning Analytics to support Teacher Inquiry: A Systematic Literature Review.- A Landscape of Learning Analytics: An Exercise to Highlight the Nature of an Emergent Field.-A Review of Recent Advances in Adaptive Assessment.- Data-driven Personalization of Student Learning Support in Higher Education.- Overcoming the MOOC data deluge with learning analytic dashboards.- A Priori Knowledge in Learning Analytics.- Knowledge Discovery from the Programme for International Student Assessment.- A Learning Analytics Approach for Job Scheduling on Cloud Servers
Автор: Carneiro Название: Deep Learning and Data Labeling for Medical Applications ISBN: 3319469754 ISBN-13(EAN): 9783319469751 Издательство: Springer Рейтинг: Цена: 6988.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.
The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.
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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