Roadmap Implement Machine Learning by Subramanian Balakrishnan (10 results)
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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More images- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. A Roadmap to Implement Machine Learning in Construction Industry | Machine Learning, Construction project | Balakrishnan Subramanian (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207487875 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Lan…dstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
- Softcover
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Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
- Softcover
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Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2024, 2024
- Softcover
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 108 pp. Englisch.
- Softcover
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Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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- Softcover
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Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Language: English
Published by LAP LAMBERT Academic Publishing Jun 2024, 2024
- Softcover
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'A Roadmap to Implement Machine Learning in Construction Industry' is a comprehensive guide that explores the application of machine learning in the construction industry. Written by industry experts, this book provides a clear roadmap…for implementing machine learning techniques in construction projects, from planning to execution. The book covers a range of topics related to machine learning, including data collection and processing, feature selection, algorithm selection, and model training and validation. It also examines the use of machine learning for various construction activities, such as project planning, risk management, quality control, and equipment maintenance. Through practical examples and case studies, the authors demonstrate the benefits of machine learning in the construction industry, such as increased efficiency, improved quality, and reduced costs. They also discuss the challenges and considerations that need to be taken into account when implementing machine learning, such as data privacy, data quality, and the need for skilled personnel.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 108 pp. Englisch.
- Softcover
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'A Roadmap to Implement Machine Learning in Construction Industry' is a comprehensive guide that explores the application of machine learning in the construction industry. Written by industry experts, this book provides a clear roadmap f…or implementing machine learning techniques in construction projects, from planning to execution. The book covers a range of topics related to machine learning, including data collection and processing, feature selection, algorithm selection, and model training and validation. It also examines the use of machine learning for various construction activities, such as project planning, risk management, quality control, and equipment maintenance. Through practical examples and case studies, the authors demonstrate the benefits of machine learning in the construction industry, such as increased efficiency, improved quality, and reduced costs. They also discuss the challenges and considerations that need to be taken into account when implementing machine learning, such as data privacy, data quality, and the need for skilled personnel.
