Model Training: Train the chosen model on the training data.
Model Evaluation: Assess model performance on the test set using appropriate metrics.
Software for Prediction: Use Python libraries (scikit-learn, TensorFlow) for modeling. Consider structural analysis software if needed (SAP2000, ETABS).
Model Deployment: Deploy the model for real-time predictions.
Continuous Improvement: Monitor and update the model as needed with new data.
Remember, quality data and iterative refinement are key to success.