This thesis, developed in collaboration with MOD - Matter Of Design, details the creation of a comprehensive data-driven platform designed to innovate the real estate workflow. The project began with a foundational phase of data engineering on AWS and the development of a Python back-end for the digitalization of business processes. The core of this work focuses on the application of machine learning models for regression and classification tasks, aimed at predicting prices and housing typologies within the Verona real estate market. The resulting integrated system provides the company with a powerful tool for market analysis and data-driven decision-making.
This thesis, developed in collaboration with MOD - Matter Of Design, details the creation of a comprehensive data-driven platform designed to innovate the real estate workflow. The project began with a foundational phase of data engineering on AWS and the development of a Python back-end for the digitalization of business processes. The core of this work focuses on the application of machine learning models for regression and classification tasks, aimed at predicting prices and housing typologies within the Verona real estate market. The resulting integrated system provides the company with a powerful tool for market analysis and data-driven decision-making.
From Data Engineering to Predictive Analytics: Development of a Data-Driven Platform for the Verona Real Estate Market with MOD - Matter Of Design
LOVATO, EMMA
2024/2025
Abstract
This thesis, developed in collaboration with MOD - Matter Of Design, details the creation of a comprehensive data-driven platform designed to innovate the real estate workflow. The project began with a foundational phase of data engineering on AWS and the development of a Python back-end for the digitalization of business processes. The core of this work focuses on the application of machine learning models for regression and classification tasks, aimed at predicting prices and housing typologies within the Verona real estate market. The resulting integrated system provides the company with a powerful tool for market analysis and data-driven decision-making.| File | Dimensione | Formato | |
|---|---|---|---|
|
Master_Thesis_EL.pdf
accesso aperto
Dimensione
38.69 MB
Formato
Adobe PDF
|
38.69 MB | Adobe PDF | Visualizza/Apri |
The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License
https://hdl.handle.net/20.500.12608/91836