Machine Learning Applications in Concrete Strength Prediction
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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 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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