Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive …
Negnevitsky shows students how to build intelligent systems drawing on techniques from knowledge-based systems, neural networks, fuzzy systems, evolutionary computation …
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on …
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Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide About This Book …
This book provides insights into how deep learning techniques impact language and speech processing applications. The authors discuss the promise, …
Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex …
Deep learning doesn't have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such …
The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations …
This book addresses the automatic sizing and layout of analog integrated circuits (ICs) using deep learning (DL) and artificial neural …
A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to …
