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Authors: Shastri, Apoorva S (2023) - This book examines the latest developments in Artificial Intelligence (AI)-based metaheuristics algorithms with applications in information security for digital media. It highlights the importance of several security parameters, their analysis, and validations for different practical applications.
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Authors: Balusamy, Balamurugan (2023) - AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems.
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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: Kolhe, Mohan Lal (2023) - This book: Discusses advances in blockchain, the Internet of Things, artificial intelligence, material structure and hybrid technologies Covers intelligent techniques in materials progression for sensor development and energy material characterization using signal processing
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Authors: Balusamy, Balamurugan (2023) - The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world.
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Authors: Balmer, Kyle (2023) - ChatGPT Business Prompt Playbook" is not just a book; it's your roadmap to crafting a passive income blog, powered by AI and affiliate marketing. Secure your copy today and embark on an exciting journey towards a lucrative online enterprise!
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Authors: Fersman, Elena (2023) - The book is written as a first person narrative, from an AI perspective, having the AI brain tell the story.
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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: Hall, Patrick (2023) - This book describes approaches to responsible AI—a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public.
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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: Rai, Amrita (2023) - This book will be a valuable resource for academicians, researchers, and professionals working in artificial intelligence/machine learning and its applications in communication and 5G.
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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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