Egor Kotov 🌐🏃♂️🚊🚋🚙Even if I don't win the #MOOD_H2020 hackathon, my takeaway is how useful
@rOpenSci #targets #rpackage https://docs.ropensci.org/targets/ is for reproducible workflows and how powerful #mlr3 https://mlr3.mlr-org.com framework is for spatial machine learning with spatiotemporal cross-validation
@rOpenSci #targets #rpackage https://docs.ropensci.org/targets/ is for reproducible workflows and how powerful #mlr3 https://mlr3.mlr-org.com framework is for spatial machine learning with spatiotemporal cross-validation
Dynamic Function-Oriented Make-Like Declarative Pipelines
Pipeline tools coordinate the pieces of computationally demanding analysis projects. The targets package is a Make-like pipeline tool for statistics and data science in R. The package skips costly runtime for tasks that are already up to date, orchestrates the necessary computation with implicit parallel computing, and abstracts files as R objects. If all the current output matches the current upstream code and data, then the whole pipeline is up to date, and the results are more trustworthy than otherwise. The methodology in this package borrows from GNU Make (2015, ISBN:978-9881443519) and drake (2018, <doi:10.21105/joss.00550>).