This repository presents a machine learning classification project focused on predicting customer churn in the telecommunications industry.

⚡ Code for machine Learning Pipeline with Scikit-learn ⚡

Churn Modelling using XGBoost

Redução da taxa de evasão de clientes (Churn Rate)

Churn prediction for banking customers using logistic regression and decision trees, implemented from scratch in R.

Churn prediction based on bank customers

Churn-modelling using Logistic Regression

Projeto realizado durante o primeiro challenge de data science da Alura.

Analyze IBM Telco Customer data to offer valuable insights for data-driven decision-making on customer retention to reduce churn

Graduation Project Repository - Bogazici University IE 492 - Spring 2024

LP3_Sem7_Computer_Engineering

This is a complete Project that revolves around churn modeling and it contains every aspect from data cleaning down to model deployment. The data of a bank was used in this implementation. An Artificial Neural Network was trained and used to predict the probability that a given customer would leave the bank(With 87% Test accuracy) and for deploy…

Customer abandonment modeling in big data

Repositório destinado a documentar o desafio de Data Science da Alura #alurachallengedatascience1

Данный проект выполнен в процессе обучения в Яндекс Практикум по программе Специалист Data Science +. Проект посвящен прогнозированию оттока клиентов банка на основе исторических данных.

Built a logistic regression based predictive model to identify customers at high risk of churn and identify the main indicators of churn.

Churn_Modelling Using Deep Learning (Implemented ANN)

Bank churn data to carry out Exploratory data analysis and Logistic regression