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 www.huber.embl.de
Modern Statistics for Modern Biology - 4 Mixture Models
| | sebastianraschka.com
Model evaluation, model selection, and algorithm selection in machine learning
1.6 parsecs away

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| | I'm an LLM Research Engineer with over a decade of experience in artificial intelligence. My work bridges academia and industry, with roles including senior staff at an AI company and a statistics professor. My expertise lies in LLM research and the development of high-performance AI systems, with a deep focus on practical, code-driven implementations.
| | www.unofficialgoogledatascience.com
Fitting Bayesian structural time series with the bsts R package
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| | by STEVEN L. SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data scien...
| | dm13450.github.io
Custom Mixtures with the dirichletprocess R package | Dean Markwick
2.8 parsecs away

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| | In my previous article I showed how you can use the dirichletprocess package for non-parametric density estimation. This time I will demonstrate how you can use the package to create your own mixture models. The ease of creating your own mixture models is the main advantage of our dirichletprocess package compared to the others out there. By using the S3 class system in R, you can easily build your own Dirichlet process mixture of what ever distribution you want.
| | mikiobraun.wordpress.com
But is it AI? - Marginally Interesting by Mikio L. Braun
21.8 parsecs away

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| One discussion I find myself in more often recently is people asking me whether something is "really AI" or not. Often, what people seem to mean with that is whether someone is already using deep learning, or still "just" machine learning. I mentioned this to a friend in the industry and he just rolled his...