An auscultation technique has been widely used in medicine as a screening examination for ages. Nowadays, advanced electronics and effective computational methods aim to support healthcare sector by providing dedicated solutions which facilitate physicians and support diagnostic process. In this paper we propose machine learning approach for analysis of heart sounds. We used acoustic signal spectral analysis to calculate feature vectors and tested a set of machine learning approaches to provide the most effective detection of cardiac disorders. Finally we achieved 91% of sensitivity and 99% of positive predictivity for a designed algorithm based on convolutional neural network.