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Best of the enterprise web
My top seven
What Google s API copyright win over Oracle means - Pundits and open sourcers are all over the place on this ruling. If you ve seen another worthwhile take on this, please add to the comments - these issues aren t going anywhere.
Have We Taken Agile Too Far? - If by too far you mean slathering agile sauce on every project like mayonnaise, then yes. Sidenote: I liked the working backwards /planning contrast via Amazon, etc.
7 Security Tasks To Automate To Match Cybersecurity Threats - Some of these may err on the side of the obvious, but you could say the same about some of the vulnerabilities being exploited.
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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: