Descargar Ebook Applied Predictive Modeling de Max Kuhn,Kjell Johnson PDF [ePub Mobi] Gratis, Comprar ebook Applied Predictive Modeling
Applied Predictive Modeling de Max Kuhn,Kjell Johnson
Descripción - Críticas “…In teaching a data science course…I use a range of different resources because I need to cover working with data, model evaluation, and machine learning methods. The next time I teach this course, I will use only this book because it covers all of these aspects of the field.” (Louis Luangkesorn, lugerpitt.blogspot.com, June 2015) “There are a wide variety of books available on predictive analytics and data modeling around the web…we’ve carefully selected the following 10 books, based on relevance, popularity, online ratings, and their ability to add value to your business. 1. Applied Predictive Modeling.” (Timothy King, Business Intelligence Solutions Review, solutions-review.com, June 2015) 'Applied Predictive Modeling aims to expose many of these techniques in a very readable and self-contained book. This is a very applied and hands-on book. It guides the reader through many examples that serve to illustrate main points, and it raises possible issues and considerations that are oftentimes overlooked or not sufficiently reflected upon. Highly recommended.' (Bojan Tunguz, tunguzreview.com, June 2015)“This monograph presents a very friendly practical course on prediction techniques for regression and classification models… It is a well-written book very useful to students and practitioners who need an immediate and helpful way to apply complex statistical techniques.” (Stan Lipovetsky, Technometrics, Vol. 56 (3), August 2014)“In my judgment, Applied Predictive Modeling by Max Kuhn and Kjell Johnson (Springer 2013) ought to be at the very top of the reading list …They come across like coaches who really, really want you to be able to do this…Applied Predictive Modeling is a remarkable text…it is the succinct distillation of years of experience of two expert modelers…” (Joseph Rickert, blog.revolutionanalytics.com, June 2014) Críticas 'This strong, technical, hands-on treatment clearly spells out the concepts, and illustrates its themes tangibly with the language R, the most popular open source analytics solution.' (Eric Siegel, Ph.D. Founder, Predictive Analytics World, Author, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die) Reseña del editor Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package.This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Contraportada This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages. Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms.Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance?all of which are problems that occur frequently in practice. The text illustrates all parts of the modeling process through many hands-on, real-life examples. And every chapter contains extensive R code for each step of the process. The data sets and corresponding code are available in the book’s companion AppliedPredictiveModeling R package, which is freely available on the CRAN archive. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. Readers and students interested in implementing the methods should have some basic knowledge of R. And a handful of the more advanced topics require some mathematical knowledge. Biografía del autor Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages. Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms.
Download applied predictive modeling pdf ebook applied predictive modeling covers the general predictive modeling course of, starting with the essential steps of data preprocessing, data splitting and foundations of mannequin tuning the textual content then supplies intuitive explanations of quite a few widespread and trendy regression and classification methods, all the time with an emphasis on illustrating and fixing actual data issues Applied predictive modeling 豆瓣 applied predictive modeling 作者 max kuhn kjell johnson 出版社 springer 出版年 2013915 页数 600 定价 usd 8995 装帧 hardcover isbn 9781461468486 Applied predictive modeling in r squarespace applied predictive modeling in r r user 2014 max kuhn, phd pfizer global rampd groton, ct maxkuhnpfizer outline conventions in r data splitting and estimating performance data preprocessing overfitting and resampling training and tuning tree models training and tuning a support vector machine
Applied predictive analytics download ebook pdf, epub applied predictive analytics download applied predictive analytics or read online books in pdf, epub, tuebl, and mobi format click download or read online button to get applied predictive analytics book now this site is like a library, use search box in the widget to get ebook that you want Ebook applied predictive modeling as pdf download portable book title applied predictive modeling name author max kuhn launching 20130517 info isbn link 1461468485 detail isbn code 9781461468486 number pages total 600 sheet news id 5tn8lweacaaj download file start reading full synopsis this text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them 400 libros científicos disponibles gratuitamente delta libros gratuitos más de 400 libros disponibles gratuitamente para descargar y leer libros científicos publicados por springer para materias de pregrado y postgrado
Detalles del Libro
- Name: Applied Predictive Modeling
- Autor: Max Kuhn,Kjell Johnson
- Categoria: Libros,Libros universitarios y de estudios superiores,Medicina y ciencias de la salud
- Tamaño del archivo: 16 MB
- Tipos de archivo: PDF Document
- Idioma: Español
- Archivos de estado: AVAILABLE
Descargar Applied Predictive Modeling de Max Kuhn,Kjell Johnson Libros Gratis en EPUB
Applied predictive modeling download ebook pdf, epub applied predictive modeling download applied predictive modeling or read online books in pdf, epub, tuebl, and mobi format click download or read online button to get applied predictive modeling book now this site is like a library, use search box in the widget to get ebook that you want Links applied predictive modeling applied predictive modeling is a book on the practice of modeling when accuracy is the primary goal applied predictive modeling table of contents data figures computing errata blog about links training applied predictive modeling 8545 by max kuhn Modeling predictive applied wordpress viii preface scholarship is the complete software development environment and the completesetofinstructionswhichgenerated thefigures therefore
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