This is the third and last of three interactive training sessions designed for you to learn more about supervised and unsupervised machine learning in R.
The content of these 3 sessions is linked and participants are encouraged to attend all three sessions to gain the most value and insight from the training series.
Lead Trainer: Dr Giorgia Mori, Data Science Trainer, Sydney Informatics Hub (SIH)
Format: This hybrid workshop will take place over a 2.5h morning session and it builds on this Machine Learning video and on the training sessions on regression and classification.
Learning outcomes: By the end of the workshop you should be able to:
- use EDA techniques to understand the structure and characteristics of datasets;
- use skills in data preprocessing and feature engineering to prepare data for predictive modeling tasks;
- learn how to select appropriate modeling techniques based on the nature of the data;
- explore dimensionality reduction methods such as principal component analysis (PCA);
- understand the concept of feature selection and feature extraction to reduce the complexity of datasets.
- Practice implementing dimensionality reduction techniques to address issues associated with high-dimensional data.
Who the workshop is for: This workshop is for Academic and Professional Staff, research students, and affiliates of The University of Sydney (with a valid UniKey). Please use your University of Sydney email address to register i.e. @sydney.edu.au, @uni.sydney.edu.au, etc
This workshop requires you to have:
Some knowledge of R. You should be familiar with;
- some of the core packages of the tidyverse, including dplyr and its functions for data manipulation;
- the magrittr pipe operator (%>%);
- the ggplot2 package for data visualization.
You will need a laptop with R and RStudio installed.
If you have any question please contact the trainer giorgia.mori@sydney.edu.au or the training team sih.training@sydney.edu.au.
This workshop is part of a series of data science training events. If you'd like to hear when registrations open for other events, please subscribe to Sydney Informatics Hub newsletters.
