R for AI-Driven Analytics: From Traditional Statistics to Machine Learning and Beyond

This book begins where many AI journeys should: with inference, probability, and regression. From there, it builds a seamless bridge to regularization, classification, tree-based ensembles, unsupervised learning, and deep neural networks—all implemented in R. Along the way, you’ll move from p-values to predictive validation, from point estimates to posterior distributions, and from correlation to causal reasoning.