MLE Regression ModelsMarket ModelModel AssumptionsLearning Parameters Using MLEQuantifying Parameter Uncertainty with Confidence IntervalsPredicting and Simulating Model OutputsProbabilistic Linear EnsemblesPrior Probability Distributions P(a, b, e)Likelihood Function P(Y| a, b, e, X)Marginal Likelihood Function P(Y|X)Posterior Probability Distributions P(a, b, e| X, Y)Assembling PLEs with PyMC and ArviZDefine Ensemble Performance MetricsAnalyze Data and Engineer FeaturesDevelop and Retrodict Prior EnsembleTrain and Retrodict Posterior ModelTest and Evaluate Ensemble PredictionsSummaryReferencesFurther Reading