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.
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Understand why and how to perform exposure assessment;
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Understand the exposure assessment and various related methods – their strengths and limitations;
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How to use machine learning methods;
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how to use the "deeper" R package to perform the deep ensemble machine learning model.
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Part 1: Introduction of Deep ensemble machine learning (1 hour).
Presenter for part 1: Professor Yuming Guo
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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
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No requirement if you only attending session 1
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For session 2 deeper tutorial:
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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")
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If you want to follow our tutorial with the Google colab, Please make sure you have a Google Drive account.
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Click here to download Sydney data and a deeper GUI software required for the tutorial with the password "DEEPERworkshop2022".
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S1 Presentation slides from Prof. Yuming.
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S2.1 Presentation slides from Wenhua.
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S2.2 Tutorial code and illustration from Wenhua.
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S2.3 Presentation slides from Liam.
If you are having trouble with any of the documents. Please contact
wenhua.yu@monash.edu for R deeper pakcage;
liam.liu@monash.edu for deeper GUI;
yuming.guo@monash.edu for other questions.