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http://hdl.handle.net/10609/126546
Title: Federated learning network: Training distributed machine learning models with the federated learning paradigm
Author: Yáñez Parareda, Eduardo
Tutor: Freitag, Félix
Keywords: federated learning
machine learning
distributed computation
privacy
Issue Date: Jan-2021
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: 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.
Language: English
URI: http://hdl.handle.net/10609/126546
Appears in Collections:Bachelor thesis, research projects, etc.

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Federated_Learning_Network-master-project-report_EN.pdfMaster project's report5.95 MBAdobe PDFView/Open
Federated_Learning_Network-presentacion_ES.mp4Project's presentation in Spanish108.66 MBMP4View/Open
federated-learning-network-main.zipMain source code621.3 kBTextView/Open
federated-learning-simulation-main.zipSource code of the small simulator6.11 kBTextView/Open
eypTFM0121memory.pdf5.93 MBAdobe PDFView/Open

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