Making new digital musical instruments requires an instrument builder to design a "mapping" specifying how a musician's actions, sensed with sensors, should translate into control over sound. Creating mappings can be difficult and time consuming. I discuss how interactive machine learning can be used to make mappings from examples, without programming. I introduce a software tool for making these mappings, provide some examples of instruments and pieces made with interactive machine learning, and discuss how using interactive machine learning can benefit creators making musical instruments and other realtime creative interactions with sensors.