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Taschenbuch. Condition: Neu. Practical Applications of Machine Learning and AI | Medicine, Environmental Science, Transportation, and Education | Toufik Mzili (u. a.) | Taschenbuch | Englisch | 2025 | IGI Global | EAN 9798337314006 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Optimization, machine learning, and artificial intelligence are revolutionizing society, medicine, environmental science, transportation, and education. In medicine, AI-driven diagnostics and personalized treatments improve patient outcomes, while optimization streamlines resource allocation. Environmental science benefits from machine learning's ability to analyze complex datasets, enabling sustainable practices and climate predictions. In transportation, optimization enhances logistics and traffic flow, with AI powering autonomous vehicles and predictive maintenance. Across all areas, these technologies drive efficiency, innovation, and smarter decision-making. Practical Applications of Machine Learning and AI: Medicine, Environmental Science, Transportation, and Education provides deeper understanding of the complexities of optimization, machine learning and AI, examining their theoretical foundations. Furthermore, it contributes to the ongoing advancement of these fields, practical applications, and transformative potentials. Covering topics including Medical Image Segmentation, student performance prediction, and pothole detection, this book is an excellent resource for computer scientists, researchers, scholars, academicians, professionals, and more.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In today's rapidly evolving world, businesses are confronted with the complex task of streamlining their operations, utilizing machine learning to their advantage, and maneuvering through the intricacies of artificial intelligence. It has become increasingly essential to allocate resources effectively, make informed decisions based on data, and capitalize on AI technologies. However, many organizations require assistance in understanding these disciplines' theoretical principles, practical implementations, and ethical implications. Innovations in Optimization and Machine Learning serve as a comprehensive solution, offering a deep dive into optimization, machine learning, and AI. By unraveling the complexities and providing practical insights, it empowers researchers, practitioners, students, and enthusiasts to understand and contribute to advancing these fields. The book covers many topics, from evolutionary algorithms to ethical AI development, ensuring a thorough understanding of key concepts and their real-world implications.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Optimization, machine learning, and fuzzy logic are fundamental in the field of computational intelligence, each contributing to solving complex problems across various domains. Optimization techniques focus on finding the best solutions to problems by improving efficiency and minimizing resources. Machine learning enables systems to learn from data, making predictions or decisions without being programmed. Fuzzy logic deals with uncertainty and imprecision, allowing for flexible decision-making processes. Together, these theories, algorithms, and applications solve challenges in fields such as engineering, finance, and healthcare, where traditional methods often fall short. The continued application and exploration of these disciplines may unveil new possibilities for advanced problem-solving and intelligent systems. Optimization, Machine Learning, and Fuzzy Logic: Theory, Algorithms, and Applications explores optimization techniques, fuzzy logic, and their integration with machine learning. It covers fundamental concepts, mathematical foundations, algorithms, and applications, providing a holistic understanding of these domains. This book covers topics such as disease detection, deep learning, and text analysis, and is a useful resource for engineers, data scientists, medical professionals, academicians, and researchers.