General Information

Machine learning is the study and application of algorithms that learn from and make predictions on data. It has revolutionised how we find things, online and off, choose which clothes to buy, which books to read and movies to watch, - and, most critically, how we do research.

In this hands-on, live coding course, we will use the open-source statistical programming language R to introduce the overall framework of a machine learning project, from exploring and visualising the data to selecting, optimising and comparing models. We will then work through key examples of applying supervised and unsupervised learning methods.

At the end of the courses students will have a broad overview of the machine learning landscape in R, will have implemented and practiced applying (via a wide variety of hands-on exercises) some of the most commonly used approaches on tabular datasets.

Participants should then be able to apply what they have learnt to their own research data, understand some of the “jargon” used to describe machine learning approaches in their field of interest, and hopefully feel confident enough to explore and apply new methods described in the literature to their own research questions.

Please note this course will not introduce:

• Neural networks and Deep Learning (for image or textual analysis)
• Natural Language Processing for Research

As these topics are the subject of other workshops currently under development at SIH (to be run mid/late 2019). We also offer a python version of this course (next session will be delivered in April 2019).

Who: The course is aimed at researchers, including ECRs, MCRs, HDR students and others. Basic familiarity with R and the tidyverse is required. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

Where: Madsen Building ACMM Lecture Room 236. Get directions with OpenStreetMap or Google Maps.

When: Mar 18-19, 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by SIH's Code of Conduct.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

• The room is wheelchair / scooter accessible.
• Accessible restrooms are available.

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email darya.vanichkina@sydney.edu.au for more information.

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Schedule

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Setup

To participate in a SIH workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.