My model works well during training and validation.But inference results differ even with similar inputs.There’s no obvious bug in the code.It feels like something subtle is off.
Decode Trail Latest Questions
When something fails, tracing the issue takes hours.Logs are scattered across systems.Reproducing failures is painful.Debugging feels reactive.
A new column was added to the input data.No one thought it would affect the model.Suddenly, inference started failing or producing nonsense results.This keeps happening as systems evolve.
I trained a model that performed really well during experimentation and validation.The metrics looked solid, and nothing seemed off in the notebook.However, once deployed, predictions started becoming unreliable within days.I’m struggling to understand why production behavior is ...
Training data looks correct.Live predictions use the same features by name.Yet values don’t match expectations. This undermines trust in the system?
Batch predictions look reasonable.Real-time predictions don’t.Same model, same features—supposedly. Yet results differ?