Mr Chris Watkins1
1Csiro, Clayton South, Australia
As CSIRO embraces the transition into the technological age it has spawned a variety of digital initiatives designed to accelerate researchers’ application of modern digital advances to their technical domains. One such initiative is the CSIRO Data School program which has been designed to equip scientists with the tools necessary to apply defensible, reproducible data analytics to unique scientific datasets. This workshop will be built around a small part of the Data designed to introduce participants to the opportunities and challenges offered by the application of modern Machine Learning (ML) techniques.
Our C3DIS offering will first introduce ML and demystify the associated hype, provide a light overview of some useful ML approaches and, most importantly, equip attendees with the ability to verify and validate the results produced by their ML pipeline. We will highlight some common difficulties with real world datasets, how to identify these problems and how to rectify them.
The focus of the workshop will on applications to scientific datasets with examples including image data, time series data and regression problems. The workshop uses Python as it’s delivery vehicle and so some familiarity with the language will be assumed. We will be using the Google Collaboratory as a compute environment, so attendees are only required to bring a laptop with an internet connection. There will be limited support on offer should attendees wish to set up their own local environments.
Research software engineer with the Scientific Computing team at CSIRO. Chris works mostly with machine learning applications to scientific problems.