Federated learning network: Training distributed machine learning models with the federated learning paradigm
This project has two main goals. On one hand, the study of the concept of Federated Learning, which was coined 3 years ago by a team of engineers from Google. On the other hand, it is intended to develop a software which serves as a tool to create a distributed network of devices, capable of applyin...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Oberta de Catalunya (UOC) |
| Repositorio: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/126546 |
| Acceso en línea: | http://hdl.handle.net/10609/126546 |
| Access Level: | acceso abierto |
| Palabra clave: | federated learning machine learning distributed computation privacy aprenentatge federat aprenentatge automàtic privadesa computació distribuïda aprendizaje federado aprendizaje automático privacidad computación distribuida Teaching -- TFM Ensenyament -- TFM Enseñanza -- TFM |
| Sumario: | This project has two main goals. On one hand, the study of the concept of Federated Learning, which was coined 3 years ago by a team of engineers from Google. On the other hand, it is intended to develop a software which serves as a tool to create a distributed network of devices, capable of applying Federated Learning with different Machine Learning models. The result is a functional software that meets our initial purpose and can apply Federated Learning in a distributed environment, allowing us to validate in a practical way, the initial concepts of study. Throughout this project, the most important concepts of Federated Learning are presented, as well as some of the software frameworks that are starting to emerge from it. |
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