How harshh351998/earthquake-prediction works
This is a notebook-based earthquake analysis and prediction project. Its documented goal is to use regional earthquake data to predict magnitude and location. The sampled Python script reads earthquake data, prepares features, trains and validates a TensorFlow model, saves a checkpoint, then accepts a date and location/depth inputs for prediction. The tree also shows separate analysis, prediction, and visualization notebooks, but their contents were not provided, so their internal behavior and connections are uncertain. The sampled script’s data path and some training parameters appear inconsistent or undefined.
Main entry points: final_data.csv Earthquake CSV data · train model.py Interactive prediction · Earthquake Prediction.ipynb Prediction notebook · Earthquake Analysis .ipynb Earthquake analysis
Components 9
Earthquake data
- Earthquake CSV data
dataset/final_data.csv
Model workflow
- Feature preparation
Model/train model.py - Model training
Model/train model.py - Saved checkpoint
- Interactive prediction
Model/train model.py
Notebook workflows
- Earthquake analysis
Earthquake Analysis .ipynb - Prediction notebook
Earthquake Prediction.ipynb - Result visualization
Earthquake Result Visualization.ipynb
Other components
- User
Connections 9
- Earthquake CSV data → Feature preparation: provides records
Model/train model.py - Feature preparation → Model training: prepares features
Model/train model.py - Model training → Saved checkpoint: saves model
Model/train model.py - User → Interactive prediction: enters inputs
Model/train model.py - Interactive prediction → Saved checkpoint: restores model
Model/train model.py - Interactive prediction → User: prints magnitude
Model/train model.py - Earthquake CSV data → Earthquake analysis
- Earthquake CSV data → Prediction notebook
- Prediction notebook → Result visualization