• Underfitting The model is not powerful enough, resulting in bad performance on both training and test data.
    • Fix: Use a more powerful model (more layers or width)
  • Overfitting: The model is too powerful; it performs perfectly on training data but does not generalises to unseen data.
    • Fixes: Use more data, use a less powerful model (fewer parameters), stop training early, or apply regularisation