Concrete Compressive Strength Prediction Project

This project aims to predict the compressive strength of concrete based on its constituent materials and age, using machine learning regression models.

Dataset

The dataset used is the "Concrete Compressive Strength" dataset from the UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/Concrete+Compressive+Strength. The Concrete_Data.xls file was downloaded and saved as ConcreteStrengthData.csv in the data/ directory.

Features:

• Cement (component 1) - kg in a cubic meter mixture
• Blast Furnace Slag (component 2) - kg in a cubic meter mixture
• Fly Ash (component 3) - kg in a cubic meter mixture
• Water (component 4) - kg in a cubic meter mixture
• Superplasticizer (component 5) - kg in a cubic meter mixture
• Coarse Aggregate (component 6) - kg in a cubic meter mixture
• Fine Aggregate (component 7) - kg in a cubic meter mixture
• Age (day) - Day since casting when the strength was measured

Target Variable:

• Concrete compressive strength - MPa

Project Structure