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Mastering Black-Box Model Selection with Uncertainty Quantification

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Black-box models are powerful but opaque, making it hard to trust their predictions blindly. Uncertainty quantification techniques such as Bayesian methods, ensembles, and bootstrapping provide actionable confidence metrics. ExcelR’s Data Science Course in Nagpur equips students with these essential skills for high-stakes AI decision-making. https://excelrposts-bijcw.wordpress.com/2025/10/13/uncertainty-quantification-for-black-box-model-selection/

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