This SpringerBrief describes how to build a rigorous end-to-end mathematical framework for deep neural networks. The authors provide tools to represent and desc

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key FeaturesUnderstand linear alge

Over the past decade, Deep Neural Networks (DNNs) have become very popular models for processing large amounts of data because of their successful application i

Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the de

Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementa