Used Decision Tree and Support Vector Machine on Wine Dataset for classification. Interpreted, predicted, visualized and compared the results among the classifiers using Scikit-learn, NumPy, Pandas and Matplotlib. Loaded the dataset from sklearn and split it for training the model and then testing the model on unseen data. Used confusion matrix and classification report for measuring the accuracy of the prediction by the model.