Showing 7 open source projects for "multi-layer perceptron python"

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  • 1
    Appfl

    Appfl

    Advanced Privacy-Preserving Federated Learning framework

    APPFL (Advanced Privacy-Preserving Federated Learning) is a Python framework enabling researchers to easily build and benchmark privacy-aware federated learning solutions. It supports flexible algorithm development, differential privacy, secure communications, and runs efficiently on HPC and multi-GPU setups.
    Downloads: 0 This Week
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  • 2
    NErlNet

    NErlNet

    Nerlnet is a framework for research and development

    NErlNet is a research-grade framework for distributed machine learning over IoT and edge devices. Built with Erlang (Cowboy HTTP), OpenNN, and Python (Flask), it enables simulation of clusters on a single machine or real deployment across heterogeneous devices.
    Downloads: 0 This Week
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  • 3
    Substra

    Substra

    Low-level Python library used to interact with a Substra network

    An open-source framework supporting privacy-preserving, traceable federated learning and machine learning orchestration. Offers a Python SDK, high-level FL library (SubstraFL), and web UI to define datasets, models, tasks, and orchestrate secure, auditable collaborations.
    Downloads: 0 This Week
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  • 4
    Pfl Research

    Pfl Research

    Simulation framework for accelerating research

    A fast, modular Python framework released by Apple for privacy-preserving federated learning (PFL) simulation. Integrates with TensorFlow, PyTorch, and classical ML, and offers high-speed distributed simulation (7–72× faster than alternatives).
    Downloads: 0 This Week
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  • Stop Storing Third-Party Tokens in Your Database Icon
    Stop Storing Third-Party Tokens in Your Database

    Auth0 Token Vault handles secure token storage, exchange, and refresh for external providers so you don't have to build it yourself.

    Rolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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  • 5
    FATE

    FATE

    An industrial grade federated learning framework

    FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms,...
    Downloads: 0 This Week
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  • 6
    NVIDIA FLARE

    NVIDIA FLARE

    NVIDIA Federated Learning Application Runtime Environment

    NVIDIA Federated Learning Application Runtime Environment NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration. NVIDIA FLARE is built on a componentized architecture that allows you to take federated...
    Downloads: 0 This Week
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  • 7
    FEDML Open Source

    FEDML Open Source

    The unified and scalable ML library for large-scale training

    A Unified and Scalable Machine Learning Library for Running Training and Deployment Anywhere at Any Scale. TensorOpera AI is the next-gen cloud service for LLMs & Generative AI. It helps developers to launch complex model training, deployment, and federated learning anywhere on decentralized GPUs, multi-clouds, edge servers, and smartphones, easily, economically, and securely. Highly integrated with TensorOpera open source library, TensorOpera AI provides holistic support of three...
    Downloads: 0 This Week
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