Automated Machine Learning: A Comprehensive Guide

<p>The book provides an introduction to the fundamentals of AutoML a comprehensive overview of the current state of the technology and detailed information about the various approaches and techniques used in AutoML. It also covers the challenges associated with AutoML as well as best practices for deploying AutoML systems. The book is divided into four parts. The first part provides an overview of the fundamentals of AutoML and its history. It explains the different types of AutoML the different algorithms used and the different challenges associated with AutoML. The second part provides an overview of the current state of AutoML including an analysis of the different approaches and techniques used. The third part provides a detailed look at the various challenges associated with AutoML including data collection and pre-processing model selection hyperparameter optimization and deployment. Finally the fourth part provides best practices for deploying AutoML systems including tips for getting the most out of AutoML. Overall this book is an invaluable resource for anyone interested in learning about AutoML. It provides a thorough introduction to the fundamentals of AutoML</p>