Astronomical data sets have been growing at an almost exponential rate, especially with the upcoming SKA, LSST, JWST, and so on, which requires the adoption of new, automated techniques for data reduction and analysis. Machine-learning methods have recently gained popularity in Astrophysics and Cosmology and may be used to perform many tasks required in the analysis of astronomical data, including: data description and interpretation, pattern recognition, prediction, classification, compression, inference and many more. For the astronomers at UWC, we are working on applying machine-learning techniques to the science exploitation of radio data from MeerKAT and upcoming SKA.