Applied Machine Learning Using mlr3 in R

This book offers a detailed exploration of advanced machine learning techniques using the mlr3 ecosystem in R, suitable for both beginners and experienced users.

The book Applied Machine Learning Using mlr3 in R provides a comprehensive overview of the mlr3 ecosystem, which consists of award-winning R packages designed for advanced machine learning applications. It emphasizes flexible and robust methodologies, guiding readers through the implementation of these techniques in R. The content is structured to cover essential machine learning tasks, including the construction and evaluation of predictive models, as well as hyperparameter tuning to maximize performance.

In Applied Machine Learning Using mlr3 in R, readers will also learn how to build sophisticated machine learning pipelines that streamline processes such as data pre-processing, modeling, and prediction aggregation. The book goes beyond the basics, delving into the extension of the mlr3 ecosystem with custom learners, measures, and pipeline components, providing a well-rounded understanding of the subject matter.

This resource is particularly beneficial for researchers, practitioners, and graduate students interested in machine learning applications. It serves not only as a textbook for introductory or advanced courses utilizing R but also as a practical reference for industry professionals conducting exploratory experiments in machine learning. With in-depth coverage of both fundamental and advanced concepts, along with ready-to-use code samples, this book is an essential tool for anyone looking to enhance their machine learning skills.