Machine learning has recently become a key computational tool for the analysis and understanding of scientific data. The talk discusses two paradigms in machine learning of great interest to the astronomical community. The first paradigm is called "transfer learning", where the idea is to exploit the existence of a data model from a similar -but not exactly the same- domain of application to the...