Angebote zu "Data" (580 Treffer)

Data Mining
39,99 € *
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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 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

Anbieter: buecher.de
Stand: 13.10.2017
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Data Mining
39,95 € *
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In den modernen Datenbanken steckt unentdecktes Wissen, das ohne geeignete Hilfsmittel kaum gefördert werden kann. Hier setzt das Data Mining an und liefert Methoden und Algorithmen, um bisher unbekannte Zusammenhänge zu entdecken. Das Buch deckt den Stoff einer einsemestrigen Vorlesung an Universitäten oder Fachhochschulen ab und ist als klassisches Lehrbuch konzipiert. Es bietet Zusammenfassungen, zahlreiche Beispiele und Übungsaufgaben. Jürgen Cleve, Uwe Lämmel ; Hochschule Wismar.

Anbieter: ciando eBooks
Stand: 11.07.2017
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Data Mining
39,95 € *
ggf. zzgl. Versand

In den modernen Datenbanken steckt unentdecktes Wissen, das ohne geeignete Hilfsmittel kaum gefördert werden kann. Hier setzt das Data Mining an und liefert Methoden und Algorithmen, um bisher unbekannte Zusammenhänge zu entdecken. Das Buch deckt den Stoff einer einsemestrigen Vorlesung an Universitäten oder Fachhochschulen ab und ist als klassisches Lehrbuch konzipiert. Es bietet Zusammenfassungen, zahlreiche Beispiele und Übungsaufgaben. Jürgen Cleve, Uwe Lämmel ; Hochschule Wismar.

Anbieter: ciando eBooks
Stand: 11.07.2017
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Business Data Communications
78,10 € *
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Business Data Communications

Anbieter: Allyouneed.com
Stand: 17.10.2017
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Data Science For Dummies
20,99 € *
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Discover how data science can help you gain in-depth insight into your business – the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles in organizations. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization’s massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you’ll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It’s a big, big data world out there – let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

Anbieter: ciando eBooks
Stand: 11.07.2017
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Metaheuristics for Big Data
91,99 € *
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Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition. The storage and management phase presents two critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires complex analysis. Here the authors propose using metaheuristics as a solution to these challenges; they are first able to deal with large size problems and secondly flexible and therefore easily adaptable to different types of data and different contexts. The use of metaheuristics to overcome some of these data mining challenges is introduced and justified in the first part of the book, alongside a specific protocol for the performance evaluation of algorithms. An introduction to metaheuristics follows. The second part of the book details a number of data mining tasks, including clustering, association rules, supervised classification and feature selection, before explaining how metaheuristics can be used to deal with them. This book is designed to be self-contained, so that readers can understand all of the concepts discussed within it, and to provide an overview of recent applications of metaheuristics to knowledge discovery problems in the context of Big Data. Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition. The storage and management phase presents two critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires complex analysis. Here the authors propose using metaheuristics as a solution to these challenges; they are first able to deal with large size problems and secondly flexible and therefore easily adaptable to different types of data and different contexts. The use of metaheuristics to overcome some of these data mining challenges is introduced and justified in the first part of the book, alongside a specific protocol for the performance evaluation of algorithms. An introduction to metaheuristics follows. The second part of the book details a number of data mining tasks, including clustering, association rules, supervised classification and feature selection, before explaining how metaheuristics can be used to deal with them. This book is designed to be self-contained, so that readers can understand all of the concepts discussed within it, and to provide an overview of recent applications of metaheuristics to knowledge discovery problems in the context of Big Data.

Anbieter: ciando eBooks
Stand: 11.07.2017
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Data Center Handbook
142,99 € *
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Data Center Handbook provides the fundamentals, technologies, and best practices in designing, constructing and managing mission critical, energy efficient data centers. • The most comprehensive single source guide ever published in this field, with 36 chapters and over 350 illustrations written by 50 world class authors • Offers disaster management techniques and lessons learned from 2011 earthquake and tsunami in Japan, and 2012 Superstorm Sandy • Discusses international standards and requirements, with contributions from experts in the United States, Canada, United Kingdom, France, Sweden, Japan, Korea, and China Hwaiyu Geng, P.E., is a consultant with Amica Association, promoting green planning, design, and construction projects. He has had over 40 years of manufacturing and management experience, working with Westinghouse, Applied Materials, HP, and Intel on multi-million high-tech projects. He has written and presented numerous technical papers at DatacenterDynamics, ASME and IIE conferences, and is also the editor/author of Manufacturing Engineering Handbook (McGraw Hill, 2004), Semiconductor Manufacturing Handbook (McGraw Hill, 2005), and Data Center Handbook (Wiley, 2014). He is a patent holder.

Anbieter: ciando eBooks
Stand: 11.07.2017
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Data Center Handbook
142,99 € *
ggf. zzgl. Versand

Data Center Handbook provides the fundamentals, technologies, and best practices in designing, constructing and managing mission critical, energy efficient data centers. • The most comprehensive single source guide ever published in this field, with 36 chapters and over 350 illustrations written by 50 world class authors • Offers disaster management techniques and lessons learned from 2011 earthquake and tsunami in Japan, and 2012 Superstorm Sandy • Discusses international standards and requirements, with contributions from experts in the United States, Canada, United Kingdom, France, Sweden, Japan, Korea, and China Hwaiyu Geng, P.E., is a consultant with Amica Association, promoting green planning, design, and construction projects. He has had over 40 years of manufacturing and management experience, working with Westinghouse, Applied Materials, HP, and Intel on multi-million high-tech projects. He has written and presented numerous technical papers at DatacenterDynamics, ASME and IIE conferences, and is also the editor/author of Manufacturing Engineering Handbook (McGraw Hill, 2004), Semiconductor Manufacturing Handbook (McGraw Hill, 2005), and Data Center Handbook (Wiley, 2014). He is a patent holder.

Anbieter: ciando eBooks
Stand: 11.07.2017
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BIG DATA. Technologieansätze im Überblick
16,99 € *
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Studienarbeit aus dem Jahr 2015 im Fachbereich Informatik - Wirtschaftsinformatik, Note: 1,3, Universität Regensburg (Lehrstuhl für Wirtschaftsinformatik I, Informationssysteme), Sprache: Deutsch, Abstract: Aktuell ist Big Data in aller Munde. Übersetzt man Big Data aus dem Englischen, lautet dies schlicht große Datenmengen. Doch große Datenmengen sind weder in der IT noch in den Geschäftsprozessen eine Neuigkeit. Neu sind die Geschwindigkeit des Wachstums des globalen Datenvolumens sowie die Anforderungen, diese zu verarbeiten und zu analysieren, um einen betriebswirtschaftlichen Nutzen daraus ziehen zu können. Zwischen den Jahren 2010 und 2020 prognostiziert man unter Experten ein weltweites Wachstum des Datenvolumens um 42% pro Jahr. Dies entspricht einer Steigerung zwischen 2010 und 2020 um mehr als das 30-Fache. Die zunehmende Digitalisierung in Unternehmen, der anhaltende Trend zu Social Media, das An-wenden von mobilen Anwendungen auf Smartphones, etc. haben zur Folge, dass das Datenvolumen, welches auch verarbeitet werden muss, rasant ansteigt. Weiter wird die Integrität und Auswertung der Datenmengen immer komplexer. Es fallen nicht mehr ausschließlich strukturierte, sondern vermehrt unstrukturierte Daten an. In Summe führt dies zu völlig neuen Anforderungen an die Skalierbarkeit, Verfügbarkeit, Flexibilität und Performanz im Datenmanagement und somit an die Informationstechnologie. Relationale Datenmodelle mit SQL als Abfragesprache sind in einigen Fällen hierzu nicht mehr die erste Wahl. Nachfolgende Arbeit definiert in Kapitel zwei den Begriff Big Data und verdeutlicht das Wirkungsprinzip sowie die Relevanz für deutsche Unternehmen. Kapitel drei widmet sich aktuellen Technologiesegmenten im Big Data-Umfeld, gibt einen Überblick zur Taxonomie verwendeter Technologien und stellt abschließend zwei Architektur- und Lösungsansätze mit Big Data im Banken- und Automobilsektor vor. Zum Schluss wird die Arbeit zusammengefasst und ein Ausblick gegeben.

Anbieter: ciando eBooks
Stand: 11.07.2017
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Data Mining and Predictive Analytics
120,99 € *
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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. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics, Second Edition : Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics, Second Edition will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives. Daniel T. Larose is Professor of Mathematical Sciences and Director of the Data Mining programs at Central Connecticut State University. He has published several books, including Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage (Wiley, 2007) and Discovering Knowledge in Data: An Introduction to Data Mining (Wiley, 2005). In addition to his scholarly work, Dr. Larose is a consultant in data mining and statistical analysis working with many high profile clients, including Microsoft, Forbes Magazine, the CIT Group, KPMG International, Computer Associates, and Deloitte, Inc. Chantal D. Larose is a Ph.D. candidate in Statistics at the University of Connecticut. Her research focuses on the imputation of missing data and model-based clustering. She has taught undergraduate statistics since 2011, and is a statistical consultant for DataMiningConsultant.com, LLC.

Anbieter: ciando eBooks
Stand: 11.07.2017
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