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Eduardo Coronado Sroka

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Jul 3, 2020

Evaluating Bayesian Mixed Models in R/Python

Learn what is meant by “posterior predictive checks” and how to visually assess model performance

Evaluating Bayesian Mixed Models in R/Python

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Eduardo Coronado Sroka

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Jun 22, 2020

A Bayesian Approach to Linear Mixed Models (LMM) in R/Python

Implementing these can be simpler than you think

A Bayesian Approach to Linear Mixed Models (LMM) in R/Python

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Jun 9, 2020

When Mixed Effects (Hierarchical) Models Fail: Pooling and Uncertainty

An intuitive and visual guide where partial-pooling becomes troublesome and Bayesian methods can help quantify uncertainty

When Mixed Effects (Hierarchical) Models Fail: Pooling and Uncertainty

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May 27, 2020

Don’t be Afraid of Nonparametric Topic Models (Part 2: Python)

Ready to up your modeling game? Dive into an easy step-by-step tutorial on how to implement/evaluate a Hierarchical Dirichlet Process model

Don’t be Afraid of Nonparametric Topic Models (Part 2: Python)

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May 12, 2020

Don’t be Afraid of Nonparametric Topic Models

Forget LDA, learn a powerful technique for uncovering an unlimited number of latent topics in text data without the headache.

Don’t be Afraid of Nonparametric Topic Models

Eduardo Coronado Sroka

Eduardo Coronado Sroka

Duke MSc Stats | Views = own | Passionate about responsible and well-founded uses of data analytics | Website: ecoronado92.github.io

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