Predictive Modeling On Concrete Dataset with EDA , Feature Engineering and With All Machine Learning Algorithms
Modeling of strength of high performance concrete using Machine Learning.
The actual concrete compressive strength (MPa) for a given mixture under a specific age (days) was determined from laboratory. Data is in raw form (not scaled).The data has 8 quantitative input variables, and 1 quantitative output variable, and 1030 instances (observations).
Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients. These ingredients include cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, and fine aggregate.
https://archive.ics.uci.edu/ml/datasets/concrete+compressive+strength