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Read later Audio version Summary: For decision makers grappling with data, Bayesian Networks are an overlooked asset. Affordable? Yes. Performance and applicability to edge devices? Yes again. Here s a practical guide to how Bayes Nets can solve enterprise problems. In part one of this series, we covered some basic probability theory principles - and compared Machine Learning approaches to Bayesian Belief Nets (Can Bayesian Networks provide answers when Machine Learning comes up short?). In this article, we ll dig a little deeper into Bayesian Belief Networks and how they can be applied to complex decisions. Understanding Bayesian Inference In my practice, I find most people involved with advanced analytics, such as predictive, data science, and ML, are familiar with the name Bayes, and can even reproduce the simple theorem below. Still, very few have any experience implementing Judea Pearl s Bayesian Belief Networks:

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