Upskilling researchers in Machine Learning

<p dir="ltr">Emerging tools and techniques in the space of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are set to change many aspects of our daily lives and research is no exception. But how do we ensure that researchers are equipped to understand and utilise these tools and techniques across the vast spectrum of research domains? </p><p dir="ltr">In this birds-of-a-feather session we aim to survey ongoing efforts around Aotearoa/New Zealand to introduce and train researchers in ML and DL, and aim to communally discuss some of the following topics: </p><ul><li>developing content and training materials; challenges in teaching and facilitating these techniques; </li><li>reaching, teaching, and engaging with a broad audience; </li><li>encouraging the growing community of practice; and </li><li>providing support for learners and practitioners through compute and other services. </li></ul><p dir="ltr">ABOUT THE AUTHORS<br>Mike Laverick is a solutions specialist for the Centre for eResearch at the University of Auckland. Formerly an atomic astrophysicist at KU Leuven, Mike now uses his experience in research and programming to help tackle the ever-growing digital needs of researchers. As part of the Rongowai mission, a collaboration between NASA and the New Zealand Space Agency, Mike has helped develop operational data workflows and visualisation tools. Mike is also a Python aficionado, helping to train and upskill researchers as a Carpentries workshop instructor. </p><p dir="ltr"><br></p><p dir="ltr">Maxime Rio is Data Research Software Engineer for NeSI and NIWA. Maxime helps researchers build data science pipelines on NeSI platforms. </p><p dir="ltr">Ben Collings is an engagement specialist at the Centre for eResearch at the University of Auckland. With a background in Physical Geography, he stumbled into the world of geographical information systems and remote sensing discovering how useful machine learning could be for resolving landcover classification problems with satellite imagery. He is completing his PhD developing new tools for coastal change detection with satellite imagery. He enjoys learning and teaching to provide researchers with tools to excel in their work and has been involved in several machine learning workshops with CeR and NeSI. </p><p dir="ltr">Dr Murray Cadzow is a Scientific Programmer within Research Teaching IT Support at the University of Otago. Prior to this he spent 11 years researching the genetic basis of gout and related diseases. Murray has been heavily involved in computational literacy and bioinformatic training at the University of Otago - organising Research Bazaar Dunedin and the Otago Bioinformatics Spring School. He is both a Carpentries instructor and instructor trainer. His teaching has focused on delivering digital literacy training to researchers, and the development and support of the local Carpentries community at Otago.</p><p dir="ltr">For more information about eResearch NZ / eRangahau Aotearoa, visit:<br><a href="https://eresearchnz.co.nz/" rel="noreferrer" target="_blank">https://eresearchnz.co.nz/</a></p>