Sistema automàtic per a la presa de decisions sobre dispositius digitals de segona mà
This thesis discusses the growing trend of online platforms enabling users worldwide to buy and sell second-hand products, particularly digital devices. The pricing of these items depends on various factors, including their age, condition, and component quality. However, many individuals wish to sel...
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| Formato: | tesis de maestría |
| Fecha de publicación: | 2023 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/401293 |
| Acesso em linha: | https://hdl.handle.net/2117/401293 |
| Access Level: | acceso abierto |
| Palavra-chave: | Data sets Machine learning Artificial intelligence data science intel·ligència artificial aprenentatge automàtic models machine learning artificial intelligence Conjunts de dades Aprenentatge automàtic Intel·ligència artificial Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
| Resumo: | This thesis discusses the growing trend of online platforms enabling users worldwide to buy and sell second-hand products, particularly digital devices. The pricing of these items depends on various factors, including their age, condition, and component quality. However, many individuals wish to sell their old electronic devices without the hassle of visiting a physical store for price estimates. This is where Artificial Intelligence (AI), particularly Machine Learning (ML), plays a pivotal role. AI has become increasingly significant across various business sectors, often operating quietly in the background. This thesis explores the idea of employing Machine Learning to provide people with estimated information and insights about their old electronic devices, eliminating the need for external consultations. To achieve this, a substantial amount of data is required. ML relies on models trained with data to make estimations about specific inputs. For instance, to extract various aspects of a digital device, a model trained on similar devices' data is necessary. These training datasets include a target variable, such as the device's price, which serves as the specific information to estimate about a second-hand device. The motivation behind this thesis is to use Machine Learning to develop and evaluate models that estimate information about second-hand market pricing information. To do so, a reliable data source is crucial. Back Market, an online marketplace specializing in refurbished electronic devices, is selected for this purpose. |
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