abdelrahmangamalomar/waze-user-churn

This repository contains projects completed as part of the Google Advanced Data Analytics Certificates. Explore real-world data analysis, Visualization, and Machine Leaning projects using Python.

Waze-User-Churn

Waze’s free navigation app makes it easier for drivers around the world to get to where they want to go. Waze’s community of map editors, beta testers, translators, partners, and users helps make each drive better and safer.

Waze project goal is to develop a machine learning model to predict user churn. Churn quantifies the number of users who have uninstalled the Waze app or stopped using the app. This project focuses on monthly user churn. An accurate model will help prevent churn, improve user retention, and grow Waze’s business. using Python and Machine Learning techniques

Built decision tree, random forest, and XGBoost to predict Waze user churn Used multiple regression to predict taxi fares, data that would be used as part of a suite of models to optimize revenue for the New York Taxi and Limousine Commission and its drivers

This project is part of my learning journey with the Google Advanced Data Analytics Certificate program.