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Tidy Modeling with R: A Framework for - Paperback, by Kuhn Max; Silge - New h
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N.º de artículo de eBay:126838814974
Última actualización el 30 ago 2025 01:49:32 H.EspVer todas las actualizacionesVer todas las actualizaciones
Características del artículo
- Estado
- Book Title
- Tidy Modeling with R: A Framework for Modeling in the Tidyverse
- ISBN
- 9781492096481
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Product Identifiers
Publisher
O'reilly Media, Incorporated
ISBN-10
1492096482
ISBN-13
9781492096481
eBay Product ID (ePID)
9057268777
Product Key Features
Number of Pages
381 Pages
Language
English
Publication Name
Tidy Modeling with R : a Framework for Modeling in the Tidyverse
Publication Year
2022
Subject
Mathematical & Statistical Software, Probability & Statistics / General, General, Data Processing
Type
Textbook
Subject Area
Mathematics, Computers
Format
Trade Paperback
Dimensions
Item Height
0.8 in
Item Weight
23.3 Oz
Item Length
9.3 in
Item Width
7.8 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2023-277763
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
001.42015118
Synopsis
Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work. RStudio engineers Max Kuhn and Julia Silge demonstrate ways to create models by focusing on an R dialect called the tidyverse. Software that adopts tidyverse principles shares both a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. You'll understand why the tidymodels framework has been built to be used by a broad range of people. With this book, you will: Learn the steps necessary to build a model from beginning to end Understand how to use different modeling and feature engineering approaches fluently Examine the options for avoiding common pitfalls of modeling, such as overfitting Learn practical methods to prepare your data for modeling Tune models for optimal performance Use good statistical practices to compare, evaluate, and choose among models, Models can be used in almost any domain for purposes including prediction, inference, or simply describing data. In all these cases, the predictive capacity of a model can be used to evaluate it, and we can build better, more useful models by adhering to good statistical practice. The tidymodels framework harmonizes the heterogeneous model interfaces in R and offers a consistent, flexible framework for modeling suitable for beginners as well as the very experienced. This book provides a practical introduction to how to use R software to create models, focusing on a dialect of the R programming language called the tidyverse. Software that adopts tidyverse principles shares a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. The tidymodels framework for modeling is built to be easily understood and used by a broad range of people.
LC Classification Number
QA76.9.Q36
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