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Federated learning is a Distributed Machine Learning model that has been used in many applications today. Most edge devices can execute models with local dataset since their computation power is unutilized.
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Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications presents the evolution, challenges, and limitations of the application of machine learning and artificial intelligence to intelligent systems and smart communities.
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A Practical Introduction to Electrical Circuits represents a fresh approach to the subject which is compact and easy to use, yet offers a comprehensive description of the fundamentals, including Kirchhoff’s laws, nodal and mesh analysis
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A Practical Introduction to Electrical Circuits represents a fresh approach to the subject which is compact and easy to use, yet offers a comprehensive description of the fundamentals, including Kirchhoff’s laws, nodal and mesh analysis
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The text discusses the integration of power electronics, renewable energy, and internet of things from the perspective of smart cities in a single volume.
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Explores the overlapping behavior of some aspects of the computational intelligence, focusing on real-life applications. It discusses how computational science... Læs mere
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With this practical guide, you'll learn how CNAPPs can help you consolidate security through DevSecOps across cloud native technologies, practices, and application lifecycles.
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Do you wish the existing books on site reliability engineering started at the beginning? Do you wish someone would walk you through how to become an SRE, how to think like an SRE, or how to... Læs mere
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Transfer Learning through Embedding Spaces provides a brief background on transfer learning and then focus on the idea of transferring knowledge through... Læs mere
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Present energy systems are undergoing a radical transformation, driven by the urgent need to address the climate change crisis. At the same time, we are witnessing the sharp growth of energy data and a revolution of advanced technologies.