Hyperparameter Tuning for Machine and Deep Learning with R

The book "Hyperparameter Tuning for Machine and Deep Learning with R" offers a comprehensive introduction to the optimization of hyperparameters for machine learning (ML) and deep learning (DL). It is aimed at practitioners in the industry as well as researchers, educators, and students in the academic world. Through a variety of practical examples, it illustrates how hyperparameter tuning can be applied in practice to achieve significant improvements in the efficiency and effectiveness of ML and DL methods. The content is divided into two main parts: theory and application. Readers gain valuable insights into how ML and DL algorithms work and learn how to achieve better results with lower costs and resources using the presented methods. The case studies are designed to be conducted on conventional desktop or laptop computers, without the need for high-performance computing.