lbollar

using ReverseDiff: GradientTape, gradient, gradient!, compile

#=
Here I am using what I would consider classical stats style of having the 
observations as rows. Julia is column major order, so it is often common
to see the observations as columns and variables as rows. With certain types
of operations, this can have major performance implications.

I was using Julia v0.5 at the time of writing this.
=#

lbollar

lbollar

lbollar

#### Log in module ###
USER <- reactiveValues(Logged = Logged)

passwdInput <- function(inputId, label) {
  tagList(
    tags$label(label),
    tags$input(id = inputId, type="password", value="")
  )
}