Exploring the use of Machine Learning with extragalactic emission-line surveys, in preparation for the Square Kilometre Array

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The Atacama Large Millimeter/submillimeter Array (ALMA) is the largest scale operating telescope project in the world. This revolutionary facility is producing over a petabyte of data a year, much of which will never be inspected by eye. Machine learning and data based approaches to exploiting this vast data archive are clearly required, For instance developing robust unsupervised algorithms for automated source/line detection, and innovative calibration algorithms based on machine learning.