Aplicación de herramientas de ML a la predicción de tendencias en función del análisis de históricos de ventas B2B
ABSTRACT: Machine learning has untapped potential in many branches of knowledge. Moreover, this potential can be used in applications of interest to companies in different sectors. This paper discusses the applications of Artificial Intelligence in demand forecasting in the B2B textile sector. This...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/24928 |
| Acceso en línea: | http://hdl.handle.net/10902/24928 |
| Access Level: | acceso abierto |
| Palabra clave: | Time Series Supervised Learning Machine Learning Series Temporales Aprendizaje Supervisado |
| Sumario: | ABSTRACT: Machine learning has untapped potential in many branches of knowledge. Moreover, this potential can be used in applications of interest to companies in different sectors. This paper discusses the applications of Artificial Intelligence in demand forecasting in the B2B textile sector. This project is coordinated and developed by Textil Santanderina, one of the leaders in the sector at national level in Spain. Therefore, this Master’s thesis in collaboration with the mentioned firm is focus on the prediction of time series with different Machine Learning techniques, and analyses the potential of the results with the aim of integrating these techniques in the company’s decision-making process. |
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