A basic challenge in quantum computing is to tune and characterise qubits on an ever-expanding scale. We have developed machine learning methods for quantum technologies, which are able to learn how to do this more efficiently than even experienced humans. This requires moving beyond methods which demand large amounts of readily available data, because in quantum technologies the data are often sparse and costly to acquire. The machine learning is required not simply to classify the measurements which have been taken but to decide what parameters to set next.