Eduardo Coronado SrokainTowards Data ScienceEvaluating Bayesian Mixed Models in R/PythonLearn what is meant by “posterior predictive checks” and how to visually assess model performanceJul 3, 20201Jul 3, 20201
Eduardo Coronado SrokainTowards Data ScienceA Bayesian Approach to Linear Mixed Models (LMM) in R/PythonImplementing these can be simpler than you thinkJun 22, 20202Jun 22, 20202
Eduardo Coronado SrokainTowards Data ScienceWhen Mixed Effects (Hierarchical) Models Fail: Pooling and UncertaintyAn intuitive and visual guide where partial-pooling becomes troublesome and Bayesian methods can help quantify uncertaintyJun 9, 20205Jun 9, 20205
Eduardo Coronado SrokainTowards Data ScienceDon’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 modelMay 27, 20204May 27, 20204
Eduardo Coronado SrokainTowards Data ScienceDon’t be Afraid of Nonparametric Topic ModelsForget LDA, learn a powerful technique for uncovering an unlimited number of latent topics in text data without the headache.May 12, 2020May 12, 2020