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 isaacslavitt.com
Isaac Slavitt: Dirichlet-multinomial model for Skittle proportions
| | austinrochford.com
Bayesian Survival Analysis in Python with pymc3 | Austin Rochford
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| | .dataframe * {border-color: #c0c0c0 !important;} .dataframe th{background: #eee;} .dataframe td{ background: #fff; text-align: right; min-width:5em; } /* Format summary rows */ .datafram
| | austinrochford.com
The Hierarchical Regularized Horseshoe Prior in PyMC3 | Austin Rochford
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| | For some time I have been interested in better understanding the horseshoe prior1 by implementing it in PyMC3. The horsehoe prior is a continuous alternative to the spike-and-slab prior for sparse Bay
| | twiecki.io
whilemy_mcmc:gently(samples) - The Best Of Both Worlds: Hierarchical Linear Regression in PyMC
3.0 parsecs away

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| | [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.
| | www.unite.ai
Generative vs. Discriminative Machine Learning Models - Unite.AI
25.7 parsecs away

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| Some machine learning models belong to either the generative or discriminative model categories. Yet what is the difference between these two categories of models? What does it mean for a model to be discriminative or generative? The short answer is that generative models are those that include the distribution of the data set, returning a []