Machine learning in optical analytics encompasses a wide range of applications in which optical instruments and analysis methods are improved by self-learning algorithms. Application examples include the quantitative determination of material composition from complex spectra, fast real-time data analysis incorporating prior knowledge, or intelligent alarm triggers. Current challenges lie in the...