Popular GitHub Repositories for Imblearn

The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

These are my notes for the interview prep workshop I led on Random Forests

Trabalho de Conclusão de Curso apresentado ao Curso de Especialização em Inteligência Artificial e Aprendizado de Máquina, como requisito parcial à obtenção do título de Especialista.

Classification task for machine laerning models to predict customer churn for a telecom company. Includes EDA, work plan, and model training/evaluation/comparison.

This project aims to train three classification models (LogisticRegression, DecisionTree and RandomForest) using AWS SageMaker to classify customer churn from a database obtained from kaggle.com.

This project focuses on predicting whether a customer will default on their credit card payment in the upcoming month. Utilizing historical transaction data and customer demographics, the project employs various machine learning algorithms to distinguish between risky and non-risky customers for better credit risk management.

Прогнозирование оттока клиентов оператора связи