Validation:
- Test the model on unseen data to assess its generalization ability
Iteration and optimization:
- Refine the model based on performance results
- May involve tuning hyperparameters or trying different algorithms
Deployment infrastructure:
- System to apply the model to new data in real-world scenarios
Monitoring and maintenance:
- Ongoing assessment of model performance
- Plan for retraining or updating as needed
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