170,99 € *

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(170,99 € / in stock)

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(170,99 € / in stock)

Regression Through Graphics: Cook

Anbieter: Hugendubel.de

Stand: 08.05.2018 Zum Angebot

Stand: 08.05.2018 Zum Angebot

164,99 € *

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(164,99 € / in stock)

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(164,99 € / in stock)

Regression Graphics:Ideas for Studying Regressions Through Graphics R. Dennis Cook

Anbieter: Hugendubel.de

Stand: 14.05.2018 Zum Angebot

Stand: 14.05.2018 Zum Angebot

179,99 € *

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(179,99 € / in stock)

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(179,99 € / in stock)

Applied Regression Computing Graphics: Cook, Weisberg

Anbieter: Hugendubel.de

Stand: 08.05.2018 Zum Angebot

Stand: 08.05.2018 Zum Angebot

170,99 € *

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(170,99 € / in stock)

Applied Regression Including Computing and Graphics: R. Dennis Cook, Sanford Weisberg

Anbieter: Hugendubel.de

Stand: 14.05.2018 Zum Angebot

Stand: 14.05.2018 Zum Angebot

23,99 € *

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Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2nd Edition provides a quick and painless way to master all the R you´ll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You´ll learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and so much more. R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. R provides a wide array of statistical and graphical techniques, and has become the standard among statisticians for software development and data analysis. R For Dummies, 2nd Edition takes the intimidation out of working with R and arms you with the knowledge and know-how to master the programming language of choice among statisticians and data analysts worldwide. * Covers downloading, installing, and configuring R * Includes tips for getting data in and out of R * Offers advice on fitting regression models and ANOVA * Provides helpful hints for working with graphics R For Dummies, 2nd Edition is an ideal introduction to R for complete beginners, as well as an excellent technical reference for experienced R programmers.

Anbieter: buecher.de

Stand: 14.06.2018 Zum Angebot

Stand: 14.06.2018 Zum Angebot

47,99 € *

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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Anbieter: buecher.de

Stand: 05.04.2018 Zum Angebot

Stand: 05.04.2018 Zum Angebot

55,99 € *

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This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book´s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for ´´wide´´ data (p bigger than n), including multiple testing and false discovery rates.

Anbieter: buecher.de

Stand: 10.06.2018 Zum Angebot

Stand: 10.06.2018 Zum Angebot

53,49 € *

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This new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggplot2, it´s easy to: produce handsome, publication-quality plots with automatic legends created from the plot specification superimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scales add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression save any ggplot2 plot (or part thereof) for later modification or reuse create custom themes that capture in-house or journal style requirements and that can easily be applied to multiple plots approach a graph from a visual perspective, thinking about how each component of the data is represented on the final plot This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e.g., importing data into R). ggplot2 is a mini-language specifically tailored for producing graphics, and you´ll learn everything you need in the book. After reading this book you´ll be able to produce graphics customized precisely for your problems, and you´ll find it easy to get graphics out of your head and on to the screen or page.

Anbieter: buecher.de

Stand: 14.06.2018 Zum Angebot

Stand: 14.06.2018 Zum Angebot

42,95 € *

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Graphics in this book are printed in black and white.Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworksscikit-learn and TensorFlowauthor Aurlien Gron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. Youll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what youve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details

Anbieter: buecher.de

Stand: 07.06.2018 Zum Angebot

Stand: 07.06.2018 Zum Angebot

38,95 € *

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Graphics in this book are printed in black and white.Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks?scikit-learn and TensorFlow?author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You´ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you´ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details

Anbieter: buecher.de

Stand: 20.05.2018 Zum Angebot

Stand: 20.05.2018 Zum Angebot