Overview

The R Way to Machine Learning: Models, Metrics, and Mastery Unlock the power of machine learning-one tidy model at a time. The R Way to Machine Learning is a comprehensive guide for students, analysts, and professionals who want to build, evaluate, and deploy machine learning models using the powerful and elegant R programming language. Centered on the modern tidymodels ecosystem, this book offers a structured, hands-on approach to understanding both the theory and practical workflows of supervised and unsupervised learning. From data preparation to model evaluation, hyperparameter tuning to deployment, readers will learn how to manage the full lifecycle of machine learning projects-cleanly, reproducibly, and with best practices in mind. What You'll Learn: Core concepts of machine learning and statistical modeling in R Step-by-step implementation of classification, regression, and clustering algorithms using tidymodels Techniques for resampling, cross-validation, and performance assessment How to tune, interpret, and compare models using reproducible workflows Methods for saving, versioning, and deploying models with vetiver Real-world examples and structured templates to accelerate your practice Whether you're transitioning from spreadsheets or already experienced in Python, this book shows how R can be your clean, composable, and professional toolset for machine learning success.

Full Product Details

9798296252807

Table of Contents

Reviews

Author Information

Tab Content 6

Countries Available