This book of Advances in Deep Learning, Artificial Intelligence and Robotics (proceedings of ICDLAIR 2020) is intended to be used as a reference by students and researchers who collect scientific and technical contributions with respect to models, tools, technologies and applica…
"Deep Learning: A Comprehensive Guide focuses on all the relevant topics in the field of Deep Learning. Covers the conceptual, mathematical and practical aspects of all relevant topics in deep learning Offers real time practical examples Provides case studies This book is aimed …
"Deep Learning: A Comprehensive Guide focuses on all the relevant topics in the field of Deep Learning. Covers the conceptual, mathematical and practical aspects of all relevant topics in deep learning Offers real time practical examples Provides case studies This book is aimed …
"Deep Learning: A Comprehensive Guide focuses on all the relevant topics in the field of Deep Learning. Covers the conceptual, mathematical and practical aspects of all relevant topics in deep learning Offers real time practical examples Provides case studies This book is aimed …
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It cove…
This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. I…
"Advanced Decision Sciences Based on Deep Learning and Ensemble Learning Algorithms: A Practical Approach Using Python describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convol…
"Advanced Decision Sciences Based on Deep Learning and Ensemble Learning Algorithms: A Practical Approach Using Python describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convol…
SMART URBAN COMPUTING APPLICATIONS
This edited book is a collection of quality research articles reporting research advances in the area of deep learning, IoT and urban computing. It describes new insights based on deep learning and IoT for urban computing and is useful for architects, engineers, policymakers, fa…
The book represents the first attempt to systematically deal with the use of deep neural networks to forecast chaotic time series. Differently from most of the current literature, it implements a multi-step approach, i.e., the forecast of an entire interval of future values. Thi…
This book is intended for students, engineers, and researchers interested in both computational mechanics and deep learning. It presents the mathematical and computational foundations of Deep Learning with detailed mathematical formulas in an easy-to-understand manner. It also d…
"This book presents the integration of machine learning and deep learning algorithms that can be applied in the healthcare sector to reduce the time needed by doctors, radiologists, and other medical professionals to analyze, predict, and diagnose conditions with accurate result…
"This book presents the integration of machine learning and deep learning algorithms that can be applied in the healthcare sector to reduce the time needed by doctors, radiologists, and other medical professionals to analyze, predict, and diagnose conditions with accurate result…
