- Event organized jointly by SSA and MAPS https://www.statsoc.org.au/event-5028135
- Workshop based on Chapt 2 and 3 of The Mathematical Engineering of Deep Learning
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The easy way to get the material is to download the zip file of this archive
-
Note book used during the workshop
- Part 1: supervised learning
- Part 2: unsupervised learning
Please make sure that you have recent R and RStudio installed.
- R : https://cran.r-project.org/
- RStudio : https://www.rstudio.com/products/rstudio/download/preview/
- R packages to be installed before workshop
install.packages("dplyr")
install.packages("ROCR")
install.packages("caret")
install.packages("ROCit")
install.packages("MASS")
install.packages("glmnet")
install.packages("tidyverse")
install.packages("ggplot2")
install.packages("ggpubr")
install.packages("animation")
install.packages("mvtnorm")
install.packages("jpeg")
install.packages("ruta")
install.packages("rARPACK")
install.packages("FactoMineR")
install.packages("keras")
install.packages("IMIFA")
install.packages("nnet")
versatile-boundaries.RData
Breast_cancer.RData
train-images.idx3-ubyt
train-labels.idx1-ubyte
t10k-images.idx3-ubyte
t10k-labels.idx1-ubyte
data-poly.Rdata
we use google collab to share code:
- Part 1: supervised learning code
- Part 2: unsupervised learning code