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#29 Model Assessment, Non-Parametric Models, And Much More, with Aki Vehtari

Learning Bayesian Statistics

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Enhancing Bayesian Workflows with Software Assistance and Diagnostics

The chapter explores a software-guided vision workflow that aids users in handling data analysis issues effectively. It emphasizes the need to bridge the gap between theoretical Bayesian resources and practical data analysis needs, focusing on diagnostic tools, model comparison, and model selection, while highlighting the importance of user comprehension and involvement in decision-making processes. Additionally, the chapter delves into challenges like overfitting, feature selection, and the dynamic nature of research in this field.

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