This is the first of three interactive training sessions designed for you to learn more about supervised and unsupervised machine learning in Python.
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.
Format: This online workshop will take place over a 2.5h morning session and it builds on the Exploratory Data Analysis and Machine Learning videos. Please watch these videos ahead of the workshop.
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;
- implement supervised machine learning algorithms for applying regression algorithms to predict continuous outcomes.
- perform model evaluation and validation to assess the performance of your regression model.
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
If you have any questions, please contact the training team at 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.
