CAR Workshop: Deep ensemble machine learning for estimating environmental exposure and beyond

Time: 10:00 AM – 13:00 PM, 8 September 2022.

It will be a hybrid workshop. Both online and on-site are welcome.

Location: 553 St Kilda Road, Melbourne.

Through the workshop, we expect you can learn:

Understand why and how to perform exposure assessment;
Understand the exposure assessment and various related methods – their strengths and limitations;
How to use machine learning methods;
how to use the "deeper" R package to perform the deep ensemble machine learning model.

Part 1: Introduction of Deep ensemble machine learning (1 hour).

Presenter for part 1: Professor Yuming Guo
Part 2: Practice on how to perform Deep ensemble machine learning using R package “deeper” (2 hours).

Tutors for part 2: Drs Alven Yu and Liam Liu

If you prefer to use your local computer, you need to install R, RStudio on your computer and make sure:
- using R (>= 3.5.0)
- installed suggested R packages: devtools,SuperLearner, caret, skimr, CAST, ranger, gbm, xgboost.
```
# check the package installation
#install.packages("pacman")
library(pacman)
p_load("devtools","SuperLearner","ranger","CAST","caret","skimr","gbm","xgboost","hexbin")
```
- installed deeper R packages with the following syntax:
```
library(devtools)
install_github("Alven8816/deeper")
```
If you want to follow our tutorial with the Google colab, Please make sure you have a Google Drive account.
Click here to download Sydney data and a deeper GUI software required for the tutorial with the password "DEEPERworkshop2022".

If you are having trouble with any of the documents. Please contact

wenhua.yu@monash.edu for R deeper pakcage;