You are building a model to predict which customer support tickets should be escalated to a senior agent.
Walk through all six phases of the ML lifecycle for this problem:
- Problem definition — what are you predicting, and what is the cost of false positives vs false negatives?
- Data collection — what data would you collect, and from where?
- Feature engineering — what features would you engineer, and how would you avoid data leakage?
- Model training and evaluation — what baseline would you use, and how would you evaluate?
- Deployment — how would you serve predictions, and what integration points are required?
- Monitoring — what specific monitoring would you set up, and what would trigger retraining?
For each phase, include at least one risk specific to this problem.