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Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condition: new. Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Add to basketHRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
Hardback. Condition: New.
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Hardback. Condition: New.
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Language: English
Published by Grid Dynamics 2022-08-12, 2022
ISBN 10: 0578328623 ISBN 13: 9780578328621
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Condition: New. 2022. hardcover. . . . . .
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Condition: 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: Brand New. 576 pages. 9.33x6.22x1.38 inches. In Stock.
Seller: AussieBookSeller, Truganina, VIC, Australia
Hardcover. Condition: new. Hardcover. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketHardcover. Condition: Brand New. 576 pages. 9.33x6.22x1.38 inches. In Stock. This item is printed on demand.
Buch. 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.