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isaacslavitt.com | ||
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www.karsdorp.io
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| | | | | I'm a researcher in Computational Humanities and Cultural Evolution at Amsterdam's [Meertens Institute](https://meertens.knaw.nl/index.php/en/), affiliated with the Royal Netherlands Academy of Arts and Sciences. I study aspects of cultural change and experiment with methods to quantify cultural diversity. A significant aspect of my recent work is understanding and accounting for biases in these quantifications. I like to use computational models from fields such as Machine Learning, Cultural Evolution, and Ecology to aid these investigations. Beyond research, I have a passion for teaching computer programming, especially within the Humanities context. Together with [Mike Kestemont](http://mikekestemont.github.io/) and [Allen Riddell](https://www.ariddell.or... | |
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weisser-zwerg.dev
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| | | | | Monte Carlo funamental concepts. | |
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twiecki.io
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| | | | | [AI summary] This blog post discusses hierarchical linear regression in PyMC3, highlighting its advantages over non-hierarchical Bayesian modeling. The author explores how hierarchical models can effectively handle multi-level data by leveraging the 'shrinkage-effect', which improves predictions by borrowing strength from related groups. Using the radon dataset, the post compares individual and hierarchical models, demonstrating that the hierarchical approach provides more accurate and robust estimates, especially in cases with limited data. The key takeaway is that hierarchical models balance individual and group-level insights, offering the best of both worlds in data analysis. | |
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aurimas.eu
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| | | a.k.a. why you should (not ?) use uninformative priors in Bayesian A/B testing. | ||
