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The aim of this work was the classification of milk samples with the use of Support Vector Machine networks. An electronic tongue, based on a sensor array of miniaturized solid-state potentiometric electrodes, was used for measurements of milk originating from various dairies (i.e. various brands) and with different fat content. The sensors were mounted into the measurement flow-cell developed at Warsaw University of Technology. Their signals were input to the Support Vector Machine neural network without a pre-processing stage. The results of the classification of milk by trademark and by fat content proved the proposed system to be very efficient.