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ORCID: https://orcid.org/0009-0005-0396-9575, Bordel Sánchez, Borja
ORCID: https://orcid.org/0000-0001-7815-5924, Souissi, Riad
ORCID: https://orcid.org/0000-0002-3793-5585 and AL-Qurishi, Muhammad
ORCID: https://orcid.org/0000-0002-7594-7325
(2024).
pyStudio: An Open-Source Machine Learning Platform.
En: "15th IEEE/ACM Annual International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2023)", 06-09 Nov 2023, Kusadasi, Turquía. ISBN 979-8-4007-0409-3. pp. 436-440.
https://doi.org/10.1145/3625007.3632288.
| Título: | pyStudio: An Open-Source Machine Learning Platform |
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| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | 15th IEEE/ACM Annual International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2023) |
| Fechas del Evento: | 06-09 Nov 2023 |
| Lugar del Evento: | Kusadasi, Turquía |
| Título del Libro: | Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining |
| Título de Revista/Publicación: | PROCEEDINGS OF THE 2023 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING, ASONAM 2023 |
| Fecha: | 14 Marzo 2024 |
| ISBN: | 979-8-4007-0409-3 |
| ISSN: | 24739928 |
| Materias: | |
| Escuela: | E.T.S.I. de Sistemas Informáticos (UPM) |
| Departamento: | Sistemas Informáticos |
| Licencias Creative Commons: | Ninguna |
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Data analytics has emerged as a critical capability for businesses and organizations in the modern era. The abundance of data necessitates a deep understanding and the exploitation of its potential to gain insights into current and future scenarios. This paper introduces an integrated platform designed to streamline data acquisition, storage, management, processing, and visualization. The primary objective is to facilitate data analysis by offering a machine learning studio equipped with pre-built algorithms. Remarkably, this platform eliminates the need for coding, allowing users to effortlessly generate AI models. Furthermore [19], it provides a secure environment for sharing these models without compromising data privacy-a noteworthy contribution in the realm of federated learning (FL). The platform's significance lies in its ability to empower non-technical users to perform advanced tasks without requiring specialized expertise.
| ID de Registro: | 85693 |
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| Identificador DC: | https://oa.upm.es/85693/ |
| Identificador OAI: | oai:oa.upm.es:85693 |
| URL Portal Científico: | https://portalcientifico.upm.es/es/ipublic/item/10207879 |
| Identificador DOI: | 10.1145/3625007.3632288 |
| URL Oficial: | https://dl.acm.org/doi/10.1145/3625007.3632288 |
| Depositado por: | iMarina Portal Científico |
| Depositado el: | 14 Ene 2025 17:43 |
| Ultima Modificación: | 14 Ene 2025 17:43 |
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