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

阿塔卡马大型毫米波/亚毫米波阵列（ALMA）是世界上规模最大的望远镜项目。这个革命性的设备每年产生超过1拍字节的数据，其中大部分是肉眼无法检查的。显然需要机器学习和基于数据的方法来利用这一庞大的数据档案，例如开发用于自动源/线检测的鲁棒无监督算法，以及基于机器学习的创新校准算法。

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.