This volume develops an effective theory approach to understanding deep neural networks of practical relevance.

This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying thei

Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techni

Over the last decade, progress in deep learning has had a profound and transformational effect on many complex problems, including speech recognition, machine t