Clasificación de clientes potenciales de servicios financieros usando técnicas de minería de datos y marketing sectorial

Abstract

This work seeks to approach sorting potential customers topic, too known as Clustering, for the digital housing product of Banco de Bogotá, you will find important topics like machine learning, unsupervised learning, data mining, similarity measures and clustering methods, moreover the reader will find the process which was implemented for develop a software tool made in python, whose allows you to do analysis of data about information that have from prospective client of bank (age, salary, education level, marital status) and how use for group them in groups with common characteristics. Finally, you will find the results next to conclusions which were obtained through develop of work.