You are building a text classification system and need to take it from raw text to a deployable model. The data is messy, labels may be imbalanced, and you need a practical approach that covers preprocessing, modeling, and evaluation. A good answer should show how you would move from a simple baseline to a stronger transformer-based model.
How would you approach a text classification problem end to end?