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Añadir al carritoTaschenbuch. Condición: Neu. Next-Gen AI: concepts, Tools, and Research perspectives | Exploring Artificial Intelligence in Research and Industry | A. Bhuvaneshwari (u. a.) | Taschenbuch | Englisch | 2025 | Scholars' Press | EAN 9786200696281 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Publicado por Scholars' Press Nov 2025, 2025
ISBN 10: 6200696284 ISBN 13: 9786200696281
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Añadir al carritoPaperback. Condición: new. Paperback. "Next-Gen AI: Concepts, Tools, and Research Perspectives" offers a comprehensive exploration of the evolving landscape of Artificial Intelligence. This work delves into the theoretical foundations that underpin modern AI systems, highlighting advancements in neural networks, deep learning, reinforcement learning, and generative models. It examines cutting-edge tools and platforms shaping AI research and deployment, including frameworks like TensorFlow, PyTorch, and AutoML. The paper emphasizes transformative real-world applications across diverse sectors-healthcare, education, finance, manufacturing, and governance-demonstrating AI's role in automating decision-making, enhancing efficiency, and fostering innovation. It also addresses critical research challenges such as bias, explainability, ethics, and data governance. By bridging theory, tools, and practice, this work provides valuable insights into the future trajectory of AI and its profound impact on both academic research and industry ecosystems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Publicado por Scholars' Press Nov 2025, 2025
ISBN 10: 6200696284 ISBN 13: 9786200696281
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'Next-Gen AI: Concepts, Tools, and Research Perspectives' offers a comprehensive exploration of the evolving landscape of Artificial Intelligence. This work delves into the theoretical foundations that underpin modern AI systems, highlighting advancements in neural networks, deep learning, reinforcement learning, and generative models. It examines cutting-edge tools and platforms shaping AI research and deployment, including frameworks like TensorFlow, PyTorch, and AutoML. The paper emphasizes transformative real-world applications across diverse sectors-healthcare, education, finance, manufacturing, and governance-demonstrating AI's role in automating decision-making, enhancing efficiency, and fostering innovation. It also addresses critical research challenges such as bias, explainability, ethics, and data governance. By bridging theory, tools, and practice, this work provides valuable insights into the future trajectory of AI and its profound impact on both academic research and industry ecosystems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 164 pp. Englisch.
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