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The study considers the possibility of simultaneous determination of pH and temperature values of the liquid medium from carbon dots (CD) fluorescence spectra using machine learning algorithms: linear regression, projections to latent structures, artificial neural networks, random forest, and gradient boosting. The study shows a successful application of fluorescence spectroscopy and machine learning algorithms to create a carbon nanosensor for pH and ambient temperature: the accuracy of determining the temperature and pH of aqueous media was tenths of oC and thousandths of pH units, respectively.