This project aimed to develop a predictive model for estimating the strength of cement based on various input parameters. Cement strength is a critical factor in construction projects as it determines the durability and load-bearing capacity of structures. Traditional methods of strength prediction rely heavily on empirical testing, which can be time-consuming and costly. Machine learning techniques offer an alternative approach to predict cement strength more efficiently and accurately.

💿 Installing

1. Environment setup.

conda create --prefix venv python==3.8 -y

conda activate venv/

2. Install Requirements and setup

pip install -r requirements.txt

5. Run Application

python app.py

🔧 Built with

• fastapi
• Python 3.8
• Machine learning
• Scikit learn
• 🏦 Industrial Use Cases