Earthquake-Prediction-Model-with-Machine-Learning is a Python-based machine learning project that uses historical seismic data to build a predictive model capable of estimating the likelihood or severity of future earthquakes. The project showcases how ML techniques can be applied to geophysical data for potential early warning systems.
- 🔍 Data preprocessing & feature engineering for seismic datasets
- 📊 Model training using supervised learning techniques
- 📈 Accuracy evaluation with performance metrics
- 📁 Clean and modular project structure
Earthquake-Prediction-Model-with-Machine-Learning/
├── model/
│ └── earthquake-prediction-model.py # Main ML script
├── .gitignore # Python/OS-specific ignores
├── LICENSE # Apache 2.0 License
└── README.md # You're reading it!
- Python 3.8+
- pip (Python package manager)
pip install numpy pandas scikit-learn matplotlib- Clone the repository:
git clone https://github.com/<your-username>/Earthquake-Prediction-Model-with-Machine-Learning.git
cd Earthquake-Prediction-Model-with-Machine-Learning- Navigate to the
modelfolder and run the script:
cd model
python earthquake-prediction-model.py- View model performance metrics in the terminal or export results for further analysis.
- 📌 Algorithms used: Logistic Regression / Random Forest / etc. (depending on your implementation)
- 📁 Input: Cleaned earthquake dataset (magnitude, depth, location, etc.)
- 📈 Output: Predicted earthquake occurrence or severity class
⚠️ Dataset not included in repo. You can use publicly available seismic datasets such as:
- Integrate real-time data feeds (e.g., USGS APIs)
- Improve feature selection using geospatial correlations
- Deploy the model as a Flask or Streamlit API
This project is licensed under the Apache 2.0 License – see the LICENSE file for details.
Created by nathnaelg | Powered by Python 🐍 & Machine Learning 🧠