Classification ML models for predicting customer outcomes (namely, whether they're likely to opt into email / catalog marketing) depending on customer demographics (age, proximity to store, gender, customer loyalty duration) as well as sales and shopping frequencies by department

End-to-end Rainfall Prediction pipeline using Python. Implements data cleaning, feature engineering (Season), preprocessing, and multiple ML models (Random Forest, XGBoost, SVM, KNN, Logistic Regression, Gradient Boosting) with hyperparameter tuning, evaluation, and model comparison.

Repository for the project about HR analysis. Here we will built model for prediction: who will get promotion?

Prediction of students' dropout using classification models. Data visualisation, feature selection, dimensionality reduction, model selection and interpretation, parameters tuning.