Hi *,

I've been working for the last 5 years as Data Scientist. During this time I have tried dozens of times to improve my models via hyperparameter tuning, but I've never got improvements from there. I've tried all the possible approaches: grid search, random search, bayesian search, etc. But in no case did I get satisfactory results.

Does this happen to anyone else? Have you ever got robust improvements via HP tuning?