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Machine Learning Approaches to Concrete Strength Prediction combines traditional engineering with modern data science, reshaping how we predict concrete strength. Focusing on concrete mixes that use sand, manufactured sand (M-sand), and laterite soil as fine aggregates, this book provides a practical guide to machine learning techniques like Linear Regression, Decision Trees, Random Forest, Support Vector Regression, and Gradient Boosting. With clear explanations and a real-world case study, it equips readers with the knowledge to apply data-driven approaches in construction.
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Machine Learning Applications in Concrete Strength Prediction
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LAP Lambert Academic Publishing, 2024
ISBN 10: 3659949310
ISBN 13: 9783659949319
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Machine Learning Applications in Concrete Strength Prediction
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LAP LAMBERT Academic Publishing, 2024
ISBN 10: 3659949310
ISBN 13: 9783659949319
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Machine Learning Applications in Concrete Strength Prediction
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LAP LAMBERT Academic Publishing, 2024
ISBN 10: 3659949310
ISBN 13: 9783659949319
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Machine Learning Applications in Concrete Strength Prediction
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ISBN 10: 3659949310
ISBN 13: 9783659949319
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Machine Learning Applications in Concrete Strength Prediction
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ISBN 10: 3659949310
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Machine Learning Applications in Concrete Strength Prediction
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Machine Learning Applications in Concrete Strength Prediction
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Machine Learning Applications in Concrete Strength Prediction
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Machine Learning Applications in Concrete Strength Prediction
Published by
LAP LAMBERT Academic Publishing Nov 2024, 2024
ISBN 10: 3659949310
ISBN 13: 9783659949319
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Machine Learning Approaches to Concrete Strength Prediction combines traditional engineering with modern data science, reshaping how we predict concrete strength. Focusing on concrete mixes that use sand, manufactured sand (M-sand), and laterite soil as fine aggregates, this book provides a practical guide to machine learning techniques like Linear Regression, Decision Trees, Random Forest, Support Vector Regression, and Gradient Boosting. With clear explanations and a real-world case study, it equips readers with the knowledge to apply data-driven approaches in construction.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Seller Inventory # 9783659949319
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Machine Learning Applications in Concrete Strength Prediction
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ISBN 10: 3659949310
ISBN 13: 9783659949319
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Machine Learning Approaches to Concrete Strength Prediction combines traditional engineering with modern data science, reshaping how we predict concrete strength. Focusing on concrete mixes that use sand, manufactured sand (M-sand), and laterite soil as fine aggregates, this book provides a practical guide to machine learning techniques like Linear Regression, Decision Trees, Random Forest, Support Vector Regression, and Gradient Boosting. With clear explanations and a real-world case study, it equips readers with the knowledge to apply data-driven approaches in construction. Seller Inventory # 9783659949319
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