In rstudio/tflearn: Interface to 'TensorFlow' Estimators

This collection of examples will show you how you can use tfestimators to easily construct powerful models using TensorFlow.

# list all the .Rmd files we have
files <- setdiff(list.files(pattern = "[.]Rmd$"), "index.Rmd")

# extract DESCRIPTIONs from their front-matter
descriptions <- sapply(files, function(file) {
  yaml <- rmarkdown::yaml_front_matter(file)
  yaml$description
})

# construct markdown links
examples <- sprintf(
  "[%s](%s)",
  tools::file_path_sans_ext(files),
  sprintf("%s.html", tools::file_path_sans_ext(files))
)

# construct dataset associating HTML link with description
data <- data.frame(
  Example = examples,
  Description = descriptions,
  stringsAsFactors = FALSE,
  row.names = NULL
)

# output as markdown table
knitr::kable(data, format = "markdown", row.names = FALSE)