How are you handling training data when public datasets don’t match your use case? [D]
Public datasets on HF or Kaggle can sometimes be too generic, wrong domain, wrong schema, outdated, or just not enough volume to generalize properly. Collecting real-world proprietary data takes months. What do people actually do? From what I have seen…