/Feature-Engineering-Project

Performing Extensive Feature Engineering Project For Machine Learning Projects

Primary LanguageJupyter Notebook

Feature-Engineering-Project

Performing Extensive Feature Engineering Project For Machine Learning Projects

Modeling-strength-of-high-performance-concrete-using-Machine-Learning

Problem statement

Modeling of strength of high performance concrete using Machine Learning.

Dataset Description

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).

Context

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.

References

https://archive.ics.uci.edu/ml/datasets/concrete+compressive+strength