Apress, 2019. — 182 p. — ISBN13: 978-1-4842-4239-1. 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. The overall book...
Packt Publishing, 2017. — 318 p. — ISBN: 978-1-78712-842-2. Get to grips with the basics of Keras to implement fast and efficient deep-learning models This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image...
Elektor Publication, 2022. — 248 p. Most people are increasingly confronted with the applications of Artificial Intelligence (AI). Music or video ratings, navigation systems, shopping advice, etc. are based on methods that can be attributed to this field. The term Artificial Intelligence was coined in 1956 at an international conference known as the Dartmouth Summer Research...
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