Shypd.aiThe largest open index of AI toolsfederated-learning-lib is an Open Source & Models tool that provides a Python framework for federated learning in enterprise environments. It enables distributed machine learning while retaining data locally for privacy and compliance.
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IBM federated learning is a Python framework designed for federated learning (FL) in enterprise settings. This library facilitates distributed machine learning processes where participant nodes retain their data locally, interacting through a learning protocol. It addresses critical concerns such as privacy, confidentiality, and regulatory compliance by avoiding the need to centralize data. The framework supports various machine learning models, including Deep Neural Networks (DNNs) and classic techniques like linear regression and k-means, encompassing supervised, unsupervised, and reinforcement learning approaches. It offers a wide array of fusion algorithms for combining model updates and includes fairness techniques to mitigate bias. The library is highly configurable for different computational environments, from data centers to edge devices, and is extensible to work with various ML libraries and protocols. An Experiment Manager Dashboard is also provided for orchestrating FL experiments.
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