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Theory Practice Enterprise Recipes by Katsov Ilya (29 results)
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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Add to basketCondition: New. KlappentextrnrnThis book provides a comprehensive guide to how marketing, supply chain, and production operations can be improved using deep learning and reinforcement learning methods, as well as their combination with traditional analytics and.
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Add to baskethardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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The Theory and Practice of Enterprise AI: Recipes and Reference Implementations for Marketing, Supply Chain, and Production Operations
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Add to basketHardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Hardcover. Condition: Brand New. 576 pages. 9.33x6.22x1.38 inches. In Stock. This item is printed on demand.
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a comprehensive guide to how marketing, supply chain, and production operations can be improved using deep learning and reinforcement learning methods, as well as their combination with traditional analytics and optimization approaches. The book is written for enterprise data scientists and analytics managers, and will also be useful for graduate students in operations research and applied statistics.The Theory and Practice of Enterprise AI is divided into five parts. Part I introduces basic concepts of enterprise decision automation and presents relevant deep and reinforcement learning methods. Part II presents recipes for customer analytics and personalization. Part III describes search and recommendation solutions that extensively leverage content data such as texts and images. Part IV discusses methods for price optimization and inventory management. Finally, Part V presents blueprints for anomaly detection and visual inspection that help to improve production and transportation operations. Python code examples are provided in the complementary online repository to support the reader's understanding of the implementation details.
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Advancements in deep learning, reinforcement learning, and generative AI have dramatically extended the toolkit of machine learning methods available to enterprise practitioners. This book provides a comprehensive guide to how marketing, supply chain, and production operations can be improved using these new methods, as well as their use in conjunction with traditional analytics and optimization approaches. The book is written for enterprise data scientists and analytics managers, and will also be useful for graduate students in operations research and applied statistics.The Theory and Practice of Enterprise AI is divided into five parts. Part I introduces the basic concepts of enterprise decision automation, deep learning, generative AI, large language models, and reinforcement learning methods. Part II presents recipes for customer analytics and personalization. Part III describes search, recommendations, knowledge management, and media generation solutions that are focused on content data such as texts and images. Part IV discusses methods for demand forecasting, price optimization, and inventory management. Finally, Part V presents blueprints for anomaly detection and visual inspection that help to improve production and transportation operations. Python code examples are provided in the complementary online repository to support the reader's understanding of the implementation details.
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£ 81.24
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Advancements in deep learning, reinforcement learning, and generative AI have dramatically extended the toolkit of machine learning methods available to enterprise practitioners. This book provides a comprehensive guide to how marketing, supply chain, and production operations can be improved using these new methods, as well as their use in conjunction with traditional analytics and optimization approaches. The book is written for enterprise data scientists and analytics managers, and will also be useful for graduate students in operations research and applied statistics.The Theory and Practice of Enterprise AI is divided into five parts. Part I introduces the basic concepts of enterprise decision automation, deep learning, generative AI, large language models, and reinforcement learning methods. Part II presents recipes for customer analytics and personalization. Part III describes search, recommendations, knowledge management, and media generation solutions that are focused on content data such as texts and images. Part IV discusses methods for demand forecasting, price optimization, and inventory management. Finally, Part V presents blueprints for anomaly detection and visual inspection that help to improve production and transportation operations. Python code examples are provided in the complementary online repository to support the reader's understanding of the implementation details.
