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Authors: Barthelmeß, Ulrike (2023) - Topics such as logical reasoning, knowledge and memory play just as important a role as machine learning and artificial neural networks. In the foreground is the question of what constitutes memory and thinking, what role our emotions play when we as humans move through life, through the world. A book that offers unusual perspectives on artificial intelligence.
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Authors: Sharma, Anand (2023) - This book features new and innovative research on the positive contributions of IoT and cloud technology healthcare information systems for the improvement of patient care and disease management. Highlighting the challenges and difficulties in implementing IoT and cloud technology in the healthcare field, the volume focuses on theories, systems, methods, algorithms, and applications
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Authors: Gremban, Keith (2023) - IoT for Defense and National Security covers topics on IoT security, architecture, robotics, sensing, policy, operations, and more, including the latest results from the premier IoT research initiative of the U.S. Defense Department, the Internet of Battle Things. The text also discusses challenges in converting defense industrial operations to IoT and summarizes policy recommendations for regulating government use of IoT in free societies.
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Authors: Carayannis, Elias G (2023) - The Handbook of Research on Artificial Intelligence, Innovation and Entrepreneurship focuses on theories, policies, practices, and politics of technology innovation and entrepreneurship based on Artificial Intelligence (AI). It examines when, where, how, and why AI triggers, catalyzes, and accelerates the development, exploration, exploitation, and invention feeding into entrepreneurial actions that result in innovation success.
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Authors: Pattanayak, Santanu (2023) - Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you will learn about convolutional neural networks, including new convolutional methods such as dilated convolution, depth-wise separable convolution, and their implementation.
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Authors: Lynch, Stephen (2023) - This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web"--
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Authors: Iten, Raban (2023) - This book explains modern approaches to discovering physical concepts with machine learning and elucidates their strengths and limitations. The automation of the creation of experimental setups and physical models, as well as model testing are discussed.
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Authors: Agrawal, Ambuj (2023) - The book will show how to build Machine Learning models for a variety of use cases in image recognition, video object recognition, and data prediction.
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Authors: Jia, Huijue (2023) - This is a timely book to introduce the new discoveries and ideas in neuroscience, for the next wave of more powerful AI. AI researchers are all interested in the human brain, which is more capable and energy-efficient, but do not have good reading materials from the rather separate subfields of neuroscience, all with plenty of jargons. Based on hundreds of publications from top journals, the book fills in the gap between existing computational hardware/algorithms and emerging knowledge from neuroscience.
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Authors: Cao, Jie (2023) - This book seeks to give readers with a preliminary but critical introduction and summary of e-commerce and big data analysis. This book introduces how to achieve data acquisition and pre-processing.
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