This post is about my final Udacity Data Science Nanodegree project. My choice for the development of the project was to carry out the churning forecast, which links the delivery of the project with professional demands.

Project Overview

The project is based on Kaggle’s Churn Prediction and Prevention contest (

This project aims to identify the churn generation of customers. Researches involving this subject are increasingly taking place in the development areas of companies and in academia due to the need to reduce the turnover of clients by predicting the reduction or stopping the use of services. …

The development of this project aimed to identify the churn generation of customers. The project’s motivation was to analyze patterns, trends and predictions extracted from the data using machine learning models capable of identifying the significant decrease in the use of services and products by customers. The importance of development is precisely to provide companies with the possibility to identify the decrease in consumption of their businesses and to act in order to identify the problems that caused this decrease, as well as to explore new possibilities to retain and attract new customers with differentiated services and new products.


Henrique Martins Prado

Master in Software Engineering with emphasis on the development of Data Management (DAMA-DMBOK) and data maturity analysis (DMM). Passion for strategy with data

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store