Real Estate Valuation in Buenos Aires, an Interactive Tool Development

This thesis explores the application of machine learning models for real estate valuation in Buenos Aires, aiming to develop a user-centric tool to assist buyers and investors in making informed decisions. Traditional regression models, while useful, often fail to capture the complex, nonlinear r...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autor principal: Gonzalvo, Francisco
Otros Autores: Iarussi, Emmanuel
Formato: Tesis de maestría acceptedVersion
Lenguaje:Inglés
Publicado: Universidad Torcuato Di Tella 2024
Materias:
Mercado Inmobiliario
Real-estate market
Innovación tecnológica
Technological innovation
Análisis de datos
Data Analysis
Machine Learning
Aprendizaje automático
Acceso en línea:https://repositorio.utdt.edu/handle/20.500.13098/12966
Aporte de:
Repositorio Digital Universidad Torcuato Di Tella de Universidad Torcuato Di Tella
id I57-R163-20.500.13098-12966
record_format dspace
spelling I57-R163-20.500.13098-129662024-09-11T19:32:28Z Real Estate Valuation in Buenos Aires, an Interactive Tool Development Gonzalvo, Francisco Iarussi, Emmanuel Mercado Inmobiliario Real-estate market Innovación tecnológica Technological innovation Análisis de datos Data Analysis Machine Learning Aprendizaje automático This thesis explores the application of machine learning models for real estate valuation in Buenos Aires, aiming to develop a user-centric tool to assist buyers and investors in making informed decisions. Traditional regression models, while useful, often fail to capture the complex, nonlinear relationships inherent in real estate data. Consequently, we employed advanced machine learning techniques, including XGBoost, Random Forest, and Support Vector Machines (SVM), selected for their robustness and efficiency in handling large datasets. Our input data consists of 64,358 property listings from the e-commerce platform Mercado Libre, obtained through a combination of Python scripts and the platform's own API. 2024-08-16T19:43:13Z 2024-08-16T19:43:13Z 2024 info:eu-repo/semantics/masterThesis info:ar-repo/semantics/tesis de maestría info:eu-repo/semantics/acceptedVersion https://repositorio.utdt.edu/handle/20.500.13098/12966 eng Tesis y Trabajos Finales de la Universidad Torcuato Di Tella info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-sa/2.5/ar/ 70 p. application/pdf application/pdf Ciudad Autónoma de Buenos Aires Universidad Torcuato Di Tella
institution Universidad Torcuato Di Tella
institution_str I-57
repository_str R-163
collection Repositorio Digital Universidad Torcuato Di Tella
language Inglés
orig_language_str_mv eng
topic Mercado Inmobiliario
Real-estate market
Innovación tecnológica
Technological innovation
Análisis de datos
Data Analysis
Machine Learning
Aprendizaje automático
spellingShingle Mercado Inmobiliario
Real-estate market
Innovación tecnológica
Technological innovation
Análisis de datos
Data Analysis
Machine Learning
Aprendizaje automático
Gonzalvo, Francisco
Real Estate Valuation in Buenos Aires, an Interactive Tool Development
topic_facet Mercado Inmobiliario
Real-estate market
Innovación tecnológica
Technological innovation
Análisis de datos
Data Analysis
Machine Learning
Aprendizaje automático
description This thesis explores the application of machine learning models for real estate valuation in Buenos Aires, aiming to develop a user-centric tool to assist buyers and investors in making informed decisions. Traditional regression models, while useful, often fail to capture the complex, nonlinear relationships inherent in real estate data. Consequently, we employed advanced machine learning techniques, including XGBoost, Random Forest, and Support Vector Machines (SVM), selected for their robustness and efficiency in handling large datasets. Our input data consists of 64,358 property listings from the e-commerce platform Mercado Libre, obtained through a combination of Python scripts and the platform's own API.
author2 Iarussi, Emmanuel
author_facet Iarussi, Emmanuel
Gonzalvo, Francisco
format Tesis de maestría
Tesis de maestría
acceptedVersion
author Gonzalvo, Francisco
author_sort Gonzalvo, Francisco
title Real Estate Valuation in Buenos Aires, an Interactive Tool Development
title_short Real Estate Valuation in Buenos Aires, an Interactive Tool Development
title_full Real Estate Valuation in Buenos Aires, an Interactive Tool Development
title_fullStr Real Estate Valuation in Buenos Aires, an Interactive Tool Development
title_full_unstemmed Real Estate Valuation in Buenos Aires, an Interactive Tool Development
title_sort real estate valuation in buenos aires, an interactive tool development
publisher Universidad Torcuato Di Tella
publishDate 2024
url https://repositorio.utdt.edu/handle/20.500.13098/12966
work_keys_str_mv AT gonzalvofrancisco realestatevaluationinbuenosairesaninteractivetooldevelopment
_version_ 1823894465736081408

Ejemplares similares