Dataset from Kaggle. Classification task on an imbalanced dataset where the objective is to predecit whether a customer will buy a travel insurance or not. We encoded, splitted and scaled the dataset, trained several models (SVM, XGB, Logistic Regression, KNN, Random Forest, Gradient Boosting), tunning the hyperparameters with grid search, evaluated them, and created an ensemble with the best ones. Doing this we got a F1 score of 0.72 in the test set.