Various machine learning code and pipelines, in various languages. Used also to support some of my blog posts at: kyrcha.info. Since GitHub does not render Rmd notebooks, these notebooks are rendered using Rpubs.
- Collinearity and feature selection
- Optimizing XGBoost and Random Forests with Bayesian Optimization
- Fitting modified Gompertz and Baranyi equations for bacterial growth in R - Rendered
Rendering instructions for Rmd documents.
To render Rmd in markdown:
rmarkdown::render('CollinearityAndFeatureSelection.Rmd', output_format = 'md_document')
To render Rmd in html:
rmarkdown::render('CollinearityAndFeatureSelection.Rmd', output_format = 'html_document', output_dir = './docs')