This project aims to address the challenge of predicting whether it will rain or snow in Hungary based on various meteorological variables.

What factors influence runners

Course Work on Machine Learning covering Supervised and Unsupervised Algorithms

The telecom operator Interconnect would like to forecast churn of their clients. To ensure loyalty, those who are predicted to leave will be offered promotional codes and special plans.

Predicting popularity of movies using the IMDb movies dataset with multiple regression algorithms such as XGBoost, Gradient Boosting, Regularization Regressors, and Stacking Regressor; Performed extensive data cleaning, feature engineering, and used transformation techniques such as winsorization and log-transformation

This project focuses on predicting the weather for the next day using a classification model. Both RandomForest and GradientBoosting classifiers were tested with grid search for hyperparameter tuning. The dataset used for this project is available at Kaggle.

ML - Supervised - Regression

When a customer places an order, the order may or may not be canceled later. To assist the hotel in minimizing losses it is necessary to analyze and predict the factors that lead customers to cancel their orders using machine learning model.

a project for CNCS2021

A sales predictor machine learning model.

Ensemble_classification

Entries for the Kaggle Home Credit Group credit default competition.

This repository contains code that was used to predict employee attrition using machine learning methods.

Utilizando algoritmos de classificação para criar um modelo preditivo que seja capaz de detectar fraudes de cartão de crédito.

apply machine learning algorithm, such as regression, tree methods, as well as a series of feature engineering to predict housing price

Machine Learning in Julia

Based on the result data of an ad campaign experiment (randomly split the customers into control and experiemnt group), determine in the future what types of customers should be sent promotions to optimize the profit from ad

[xgboost/ tidymodels/ bookdown] Boosting methods for regression: Theory and application in R