graduated from the Machine Learning course . There we had some theoretical and practical lessons on the following concepts: MLE, GLM, GDA, SVM, NN, Deep Learning, solution trees, ensembling, clusterization (k-means), GMM, PCA, NLP and others. The basic language used during the course was Python. My course project was based on Kaggle HR dataset (classification problem), where the following approaches were used: correlation, descriptive analysis, Random forest, MSL neural network, SVM, AdaBoost, Decision tree, Naïve Bayes, Gradient boosting, estimating metrics.