TsingZ0/FL-IoT
This is a platform containing the datasets and federated learning algorithms in IoT environments.
This platform helps researchers and data scientists studying human behavior analyze sensor data from multiple devices without centralizing private information. You can input pre-processed or raw activity monitoring sensor data, like from smartphones or wearable devices, and apply various federated learning algorithms to classify human activities. This is ideal for those working with decentralized health or activity tracking data.
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Use this if you need to train machine learning models on sensitive, distributed sensor data for activity recognition tasks while keeping the data on individual devices.
Not ideal if your data is already centralized, you are not working with sensor data for classification, or you need algorithms beyond federated learning.
Stars
72
Forks
9
Language
Python
License
MIT
Category
Last pushed
Dec 09, 2024
Commits (30d)
0
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