Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. • Master fast-paced practical deep learning concepts with math- and programming-friendly abstractions. • Design, develop, train, validate, and deploy deep neural networks using the Keras framework • Use best practices for debugging and validating deep learning models • Deploy and integrate deep learning as a service into a larger software service or product • Extend deep learning principles into other popular frameworks Software engineers and data engineers with basic programming skills in any language and who are keen on exploring deep learning for a career move or an enterprise project.