publications/LatinR2019/Presentation/Scripts/README.md

In r-tensorflow/autokeras: R Interface to 'AutoKeras'

LatinR 2019

Auto-Keras: An R easily accessible deep learning library

Dependencies

In order to reproduce this presentation steps, the following libraries must be installed:

install.packages(c(
  "abind", "dplyr", "ggplot2", "keras", "reshape2", "rstudioapi", "rvest",
  "shiny", "xfun"
))

if (!require("remotes")) {
  install.packages("remotes")
}
remotes::install_github("jcrodriguez1989/autokeras", dependencies = TRUE)

Creating the classifier

Follow the steps of each file to get:

• 01_get_data.R to download all emoji pictures from Emojipedia.
• 02_imgs_to_array.R to transform all these pictures to an R array.
• 03_fit_model.R to fit the autokeras model.
• 04_predict.R to predict categories for new emojis.

Fast Model Writing

Steps to reproduce Fast Model Writing:

1) Open RStudio 2) In the Console pane type source("presentation.R") 3) Open a New File, in the New File Source pane type the letter i and press the Tab key. It will start writing super fast on the New File. 4) After, to start typing the emojized version, in the Source pane type the letter s and press the Tab key.

Emojifier

The Emojifier is a Shiny app that will load the previously trained model. This app allows to drop any image and generate a predicted category for it.

2019 emoji trivia

The 2019 emoji trivia is a Shiny app that will show each of the 2019 new emojis and lets the user guess into which category it was classified. This Shiny app can also be found at shinyapps.io.

If the four emojis are correctly classified by the user, then as a prize it will provide a link to the Emojizer RStudio addin:

r-tensorflow/autokeras documentation built on Jan. 19, 2021, 8 a.m.