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austinrochford.com | ||
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ckrapu.github.io
A PyMC Gaussian process example with uncertain spatial coordinates |
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www.djmannion.net
Data are sometimes on a circular scale, such as the angle of an oriented stimulus, and the analysis of such data often needs to take this circularity into account. Here, we will look at how we can use PyMC to fit a model to circular data. |
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twiecki.io
[AI summary] This technical blog post explains the advantages of hierarchical Bayesian modeling over non-hierarchical approaches using a case study of predicting radon levels across different US counties with the PyMC3 library. |
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blog.ml.cmu.edu
The latest news and publications regarding machine learning, artificial intelligence or related, brought to you by the Machine Learning Blog, a spinoff of the Machine Learning Department at Carnegie Mellon University. |
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