Editing Bayesian Ml (section)

== <span style="color: #FFFFFF;">Creating</span> ==
Designing a calibrated Bayesian ML pipeline:
# For regression with small-medium data (<10k): use GP with RBF or Matérn kernel — exact calibration.
# For classification at scale: train deep ensemble of 5 models — strong calibration, high cost.
# For single-model practical calibration: train standard model, apply temperature scaling on validation set.
# For hyperparameter tuning: replace grid search with Bayesian optimization (Optuna TPE or BoTorch GP-BO).
# Monitor calibration in production: track reliability diagrams weekly and alert on ECE degradation.

[[Category:Artificial Intelligence]]
[[Category:Machine Learning]]
[[Category:Bayesian Machine Learning]]
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