Focusing on practical applications, this book minimizes theoretical concepts to provide effective algorithms for deep learning—a rapidly evolving field in various industries. It begins with foundational knowledge and progresses to evaluate algorithm performance on specific datasets, addressing real-world challenges. Richly illustrated with figures, tables, and code snippets, it offers comprehensive examples that empower readers to quickly grasp concepts and implement solutions. This resource serves as a one-stop guide for professionals seeking to navigate deep learning for object detection and classification.
