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sigel Weihnachts-Motiv-Papier , Trees, , A4, 90...
5,66 € *
zzgl. 5,22 € Versand

Feinpapier, für Inkjet/Laser/KopiererInhalt: 25 Blatt(DP090)Weihnachts-Motiv-Papier "Trees"&bull, geeignet für Inkjet-, Laserdrucker und Kopierer&bull, Feinpapier&bull, 90 g/qm&bull, Abgabe nur in ganzen VE, sWeihnachts-Motiv-Umschlag "Trees", ohne Fenster&bull, geeignet für Inkjet-, Laserdrucker und Kopierer&bull, Spezialpapier&bull, 90 g/qm&bull, gummiert&bull, Abgabe nur in ganzen VE, sHinweis:Gestalten Sie schnell und einfach online die Weihnachts-Post. Das Online-Tool print@web ermöglicht es Ihnen ganz ohne Installation oder Software-Downloadüberall - im Büro und zu Hause - Ihre Weihnachts-Papiere, -Karten und -Etiketten online unter www.sigel.de mit PC zu gestalten und mit Ihrem Drucker auszudrucken. Zudem stehen Ihnen weihnachtliche Textvorschläge, Weihnachts-Clip-Arts und -Fotos zur freien Verfügung. Ausgezeichnet auch für den Seriendruck geeignet.Anwendungsbeispiele: - perfekt für Ihre Weihnachts-Post - Gestalten Sie die Weihnachts-Post ganz individuell und versehen Sie z.B. mit Ihrem Logo oder Firmeneindruck

Anbieter: Blitec
Stand: 24.09.2020
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Mining of Massive Datasets
58,99 € *
ggf. zzgl. Versand

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

Anbieter: buecher
Stand: 24.09.2020
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Mining of Massive Datasets
58,99 € *
ggf. zzgl. Versand

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

Anbieter: buecher
Stand: 24.09.2020
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Geoff's Gardening Year: A Month-by-Month Guide ...
9,95 € *
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Geoff Hodge takes you month by month through the tasks to make your garden beautiful. With general jobs each month and detailed information about herbaceous borders, fruit bushes, vegetables, houseplants, trees, and shrubs with a plant of the month and an analysis of a garden tool each month. An essential guide from an horticultural expert, past editor of Garden News, web editor for the Royal Horticultural Society, and contributor to Radio Gardening. 1. Language: English. Narrator: Geoff Hodge. Audio sample: http://samples.audible.de/bk/rdga/000002/bk_rdga_000002_sample.mp3. Digital audiobook in aax.

Anbieter: Audible
Stand: 24.09.2020
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Mining of Massive Datasets
83,40 € *
ggf. zzgl. Versand

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

Anbieter: Dodax
Stand: 24.09.2020
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An Introduction to Kolmogorov Complexity and It...
85,59 € *
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This must-read textbook presents an essential introduction to Kolmogorov complexity (KC), a central theory and powerful tool in information science that deals with the quantity of information in individual objects. The text covers both the fundamental concepts and the most important practical applications, supported by a wealth of didactic features.This thoroughly revised and enhanced fourth edition includes new and updated material on, amongst other topics, the Miller-Yu theorem, the Gács-Kucera theorem, the Day-Gács theorem, increasing randomness, short lists computable from an input string containing the incomputable Kolmogorov complexity of the input, the Lovász local lemma, sorting, the algorithmic full Slepian-Wolf theorem for individual strings, multiset normalized information distance and normalized web distance, and conditional universal distribution.Topics and features: describes the mathematical theory of KC, including the theories of algorithmic complexity and algorithmic probability, presents a general theory of inductive reasoning and its applications, and reviews the utility of the incompressibility method, covers the practical application of KC in great detail, including the normalized information distance (the similarity metric) and information diameter of multisets in phylogeny, language trees, music, heterogeneous files, and clustering, discusses the many applications of resource-bounded KC, and examines different physical theories from a KC point of view, includes numerous examples that elaborate the theory, and a range of exercises of varying difficulty (with solutions), offers explanatory asides on technical issues, and extensive historical sections, suggests structures for several one-semester courses in the preface.As the definitive textbook on Kolmogorov complexity, this comprehensive and self-contained work is an invaluable resource for advanced undergraduate students, graduate students, and researchers in all fields of science.

Anbieter: Dodax
Stand: 24.09.2020
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Data Mining and Statistics for Decision Making
128,00 CHF *
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Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized linear models, regularized regression, PLS regression, decision trees, neural networks, support vector machines, Vapnik theory, naive Bayesian classifier, ensemble learning and detection of association rules. They are discussed along with illustrative examples throughout the book to explain the theory of these methods, as well as their strengths and limitations. Key Features: * Presents a comprehensive introduction to all techniques used in data mining and statistical learning, from classical to latest techniques. * Starts from basic principles up to advanced concepts. * Includes many step-by-step examples with the main software (R, SAS, IBM SPSS) as well as a thorough discussion and comparison of those software. * Gives practical tips for data mining implementation to solve real world problems. * Looks at a range of tools and applications, such as association rules, web mining and text mining, with a special focus on credit scoring. * Supported by an accompanying website hosting datasets and user analysis. Statisticians and business intelligence analysts, students as well as computer science, biology, marketing and financial risk professionals in both commercial and government organizations across all business and industry sectors will benefit from this book.

Anbieter: Orell Fuessli CH
Stand: 24.09.2020
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Data Mining and Statistics for Decision Making
75,00 CHF *
ggf. zzgl. Versand

Data mining is the process of automatically searching large volumesof data for models and patterns using computational techniques fromstatistics, machine learning and information theory; it is theideal tool for such an extraction of knowledge. Data mining isusually associated with a business or an organization's need toidentify trends and profiles, allowing, for example, retailers todiscover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of datamining, such as clustering, discriminant analysis, logisticregression, generalized linear models, regularized regression, PLSregression, decision trees, neural networks, support vectormachines, Vapnik theory, naive Bayesian classifier, ensemblelearning and detection of association rules. They are discussedalong with illustrative examples throughout the book to explain thetheory of these methods, as well as their strengths andlimitations. Key Features: * Presents a comprehensive introduction to all techniques usedin data mining and statistical learning, from classical to latesttechniques. * Starts from basic principles up to advanced concepts. * Includes many step-by-step examples with the main software (R,SAS, IBM SPSS) as well as a thorough discussion and comparison ofthose software. * Gives practical tips for data mining implementation to solvereal world problems. * Looks at a range of tools and applications, such asassociation rules, web mining and text mining, with a special focuson credit scoring. * Supported by an accompanying website hosting datasets and useranalysis. Statisticians and business intelligence analysts, students aswell as computer science, biology, marketing and financial riskprofessionals in both commercial and government organizationsacross all business and industry sectors will benefit from thisbook.

Anbieter: Orell Fuessli CH
Stand: 24.09.2020
Zum Angebot
Data Mining and Statistics for Decision Making
75,00 CHF *
ggf. zzgl. Versand

Data mining is the process of automatically searching large volumesof data for models and patterns using computational techniques fromstatistics, machine learning and information theory; it is theideal tool for such an extraction of knowledge. Data mining isusually associated with a business or an organization's need toidentify trends and profiles, allowing, for example, retailers todiscover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of datamining, such as clustering, discriminant analysis, logisticregression, generalized linear models, regularized regression, PLSregression, decision trees, neural networks, support vectormachines, Vapnik theory, naive Bayesian classifier, ensemblelearning and detection of association rules. They are discussedalong with illustrative examples throughout the book to explain thetheory of these methods, as well as their strengths andlimitations. Key Features: * Presents a comprehensive introduction to all techniques usedin data mining and statistical learning, from classical to latesttechniques. * Starts from basic principles up to advanced concepts. * Includes many step-by-step examples with the main software (R,SAS, IBM SPSS) as well as a thorough discussion and comparison ofthose software. * Gives practical tips for data mining implementation to solvereal world problems. * Looks at a range of tools and applications, such asassociation rules, web mining and text mining, with a special focuson credit scoring. * Supported by an accompanying website hosting datasets and useranalysis. Statisticians and business intelligence analysts, students aswell as computer science, biology, marketing and financial riskprofessionals in both commercial and government organizationsacross all business and industry sectors will benefit from thisbook.

Anbieter: Orell Fuessli CH
Stand: 24.09.2020
Zum Angebot