Tidy Modeling with R - A Framework for Modeling in the Tidyverse

"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 adops 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"--

About the author

Max Kuhn is a software engineer at RStudio. He is currently working on improving R's modeling capabilities. He was applying models in the pharmaceutical and diagnostic industries for over 18 years. Max has a Ph.D. in Biostatistics and is the author of numerous R packages for techniques in machine learning. He, and Kjell Johnson, wrote the book "Applied Predictive Modeling", which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015. Their second book, "Feature Engineering and Selection", was published in 2019.

Product details

• Authors: Max Kuhn, Kuhn Max, Julia Silge
• Publisher: O'Reilly
• Languages: English
• Product format: Paperback / Softback
• Released: 31.08.2022
• EAN: 9781492096481
• ISBN: 978-1-4920-9648-1
• Dimensions: 177 mm x 233 mm x 20 mm
• Weight: 658 g
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; MATHEMATICS / Probability & Statistics / General, COMPUTERS / Mathematical & Statistical Software, COMPUTERS / Computer Simulation, Probability & statistics, Mathematical & statistical software, Probability and statistics, COMPUTERS / Data Science / General, Mathematical and statistical software, Data capture and analysis, Data Capture & Analysis