This is a simple web application that predicts the compressive strength of concrete based on its mix components. It is built using Python, Machine Learning, and Streamlit.
The app allows users to input concrete mix details such as:
- Cement
- Blast Furnace Slag
- Fly Ash
- Water
- Superplasticizer
- Coarse Aggregate
- Fine Aggregate
- Age of Concrete (days)
It predicts the compressive strength of the concrete (MPa) using a machine learning regression model.
- Machine Learning-based prediction
- Civil Engineering relevance
- User-friendly web interface via Streamlit
- Public dataset from UCI Machine Learning Repository
- Python
- Streamlit
- Scikit-learn
- Pandas
- Numpy
- Clone the repository:
git clone https://github.com/yourusername/Concrete-Strength-Predictor.git- Install the dependencies:
pip install -r requirements.txt- Run the Streamlit app:
streamlit run concrete_strength_app.pyConcrete Compressive Strength Data Set
