Modelo predictivo para precios de viviendas en la ciudad de Guayaquil mediante Machine Learning

Abstract

The city of Guayaquil in Ecuador, being currently a large city in extension, the real value of a house must be understood. This proposal arises from the need to build a model capable of predicting housing prices in a reliable, accurate and useful way. For this, it is necessary to combine the collection of real data obtained from real estate portals with the use of analysis and machine learning techniques. In addition, geospatial visualization using Google Maps to determine features will allow us to observe the context surrounding the homes, such as parks, schools, hospitals or shopping centers that must be considered when analyzing. The objective of this work is to model a technical tool that offers real values to those who wish to buy, sell or plan housing in Guayaquil, facilitating decision making with the use of Google Maps.