Introduction to Machine Learning
This workshop will introduce machine learning concepts through a mixture of lecture and hands-on coding. The aim is to teach a basic understanding of designing machine learning workflows for supervised and unsupervised learning approaches, classification and regression methods and model tuning. The workshop will be taught by Dr. Kevin Chai and Dr. Rebecca Lange from the Curtin Institute for Computation.
Who: The course is aimed at postgraduate students, researchers and professionals looking at taking their analytics skills to the next level.
Prerequisites: A working knowledge of Python and Jupyter notebooks is essential for this workshop. i.e. knowledge of basic data structures, operations and how to write scripts. The notebooks used throughout the workshop have been developed to be compatible with Python 2.7x and 3.x but may require some Python packages to be updated to the most recent version (e.g. scikit-learn). No prior knowledge of machine learning is expected.
Content: We will be giving a general overview on machine learning followed by worked examples of how to build machine learning pipelines.
- Data preparation
- Exploratory data analysis
- Cross validation
- Learning curves
- Model tuning
- Dimensionality reduction
RVSP: You can register via Eventbrite, there is a small registration fee which will cover morning and afternoon tea.
Contact: Please email firstname.lastname@example.org for more information.
If you have any special requirements to enable you to participate at this event please advise when you RSVP or email the Curtin Institute for Computation. We will contact you to provide assistance.
For information about disability services at Curtin, please visit disability.curtin.edu.au.