🏗️ Cement Compressive Strength Prediction

This project predicts the compressive strength of concrete using a linear regression model based on chemical composition and age.

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📊 Overview

The dataset contains various input parameters like:

• Cement, Fly Ash, Water content
• Aggregates and Additives
• Curing Age

The model predicts the final compressive strength in MPa.

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🛠️ Technologies Used

• Python
• Pandas
• Scikit-learn

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🚀 How to Run

• git clone https://github.com/nikgarhwal/cement_strength_probability.git

• cd cement_strength_probability

• pip install -r requirements.txt

• python cement_strength_predictor.py

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💬 Sample Interaction

• 📊 Model Evaluation:

  • MAE: 8.11
  • MAPE: 30.61%
  • MSE: 105.97

• 🏗️ Predict Cement Compressive Strength

  • Cement (kg in a m^3 mixture) (range: 102.00 – 540.00): 350
  • Water (kg in a m^3 mixture) (range: 121.75 – 247.00): 190
  • ...
  • 🧾 Estimated Cement Strength: 27.15 MPa

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