Описание: Getting numbers is easy; getting trustworthy numbers is hard. From experimentation leaders at Amazon, Google, LinkedIn, and Microsoft, this guide to accelerating innovation using A/B tests includes practical examples, pitfalls, and advice for students and industry professionals, plus deeper dives into advanced topics for experienced practitioners.
Автор: Kumar A. V. Senthil Название: Web Usage Mining Techniques and Applications Across Industries ISBN: 1522506136 ISBN-13(EAN): 9781522506133 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 29106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Web usage mining is defined as the application of data mining technologies to online usage patterns as a way to better understand and serve the needs of web-based applications. Because the internet has become a central component in information sharing and commerce, having the ability to analyze user behavior on the web has become a critical component to a variety of industries.Web Usage Mining Techniques and Applications Across Industries addresses the systems and methodologies that enable organizations to predict web user behavior as a way to support website design and personalization of web-based services and commerce. Featuring perspectives from a variety of sectors, this publication is designed for use by IT specialists, business professionals, researchers, and graduate-level students interested in learning more about the latest concepts related to web-based information retrieval and mining.
Автор: Bhattacharyya Siddhartha, Banerjee Pinaki, Majumdar Dipankar Название: Handbook of Research on Advanced Hybrid Intelligent Techniques and Applications ISBN: 1466694742 ISBN-13(EAN): 9781466694743 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 41580.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Conventional computational methods, and even the latest soft computing paradigms, often fall short in their ability to offer solutions to many real-world problems due to uncertainty, imprecision, and circumstantial data. Hybrid intelligent computing is a paradigm that addresses these issues to a considerable extent.The Handbook of Research on Advanced Research on Hybrid Intelligent Techniques and Applications highlights the latest research on various issues relating to the hybridization of artificial intelligence, practical applications, and best methods for implementation. Focusing on key interdisciplinary computational intelligence research dealing with soft computing techniques, pattern mining, data analysis, and computer vision, this book is relevant to the research needs of academics, IT specialists, and graduate-level students.
Описание: This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc.
Автор: Skopik Florian, Wurzenberger Markus, Landauer Max Название: Smart Log Data Analytics: Techniques for Advanced Security Analysis ISBN: 3030744493 ISBN-13(EAN): 9783030744496 Издательство: Springer Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides insights into smart ways of computer log data analysis, with the goal of spotting adversarial actions.
Автор: Chang Название: Service Mining: Framework And Application ISBN: 1606495747 ISBN-13(EAN): 9781606495742 Издательство: McGraw-Hill Рейтинг: Цена: 3252.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The shifting focus of service from the 1980s to 2000s has proved that IT not only lowers the cost of service but creates avenues to enhance and increase revenue through service. The new type of service, e-service, is mobile, flexible, interactive, and interchangeable. While service science provides an avenue for future service researches, the specific research areas from the IT perspective still need to be elaborated. This book introduces a novel concept-service mining-to address several research areas from technology, model, management, and application perspectives. Service mining is defined as "a systematical process including service discovery, service experience, service recovery, and service retention to discover unique patterns and exceptional values within the existing services." The goal of service mining is similar to data mining, text mining, or web mining, and aims to "detect something new" from the service pool. The major difference is the feature of service is quite distinct from the mining target, like data or text. This book devises concepts of service mining and identifies the possible applications. The author provides a roadmap of service mining to researchers, managers, and marketers in service sectors.
Автор: Li Deren, Wang Shuliang, Li Deyi Название: Spatial Data Mining: Theory and Application ISBN: 3662569361 ISBN-13(EAN): 9783662569368 Издательство: Springer Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: To address the spatiotemporalspecialties of spatial data, the authors introduce the key concepts andalgorithms of the data field, cloud model, mining view, and Deren Li methods.
Автор: Mariana Curado Malta, Ana Alice Baptista, Paul Walk Название: Developing Metadata Application Profiles ISBN: 1522522212 ISBN-13(EAN): 9781522522218 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 24809.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Discusses the latest trends and techniques for effectively managing and exchanging metadata. Including a range of perspectives on schemas and application profiles, such as interoperability, ontology-based design, and model-driven approaches, this book is designed for researchers, academics, professionals, graduate students, and practitioners actively engaged in data science.
Автор: Obaid Ahmed J., Polkowski Zdzislaw, Bhushan Bharat Название: Advanced Practical Approaches to Web Mining Techniques and Application ISBN: 1799894274 ISBN-13(EAN): 9781799894278 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 30908.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Illustrates all the concepts of web mining and fosters transformative, multidisciplinary, and novel approaches that introduce the practical method of analysing various web data sources and extracting knowledge by taking into consideration the unique challenges present in the environment.
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
Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>
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.
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