Showing 14 open source projects for "python-4suite-xml"

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  • Dun and Bradstreet Connect simplifies the complex burden of data management Icon
    Dun and Bradstreet Connect simplifies the complex burden of data management

    Our self-service data management platform enables your organization to gain a complete and accurate view of your accounts and contacts.

    The amount, speed, and types of data created in today’s world can be overwhelming. With D&B Connect, you can instantly benchmark, enrich, and monitor your data against the Dun & Bradstreet Data Cloud to help ensure your systems of record have trusted data to fuel growth.
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  • D&B Hoovers is Your Sales Accelerator Icon
    D&B Hoovers is Your Sales Accelerator

    For sales teams that want to accelerate B2B sales with better data

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  • 1
    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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  • 2
    FLEXible

    FLEXible

    Federated Learning (FL) experiment simulation in Python

    FLEXible (Federated Learning Experiments) is a Python framework offering tools to simulate FL with deep learning. It includes built-in datasets (MNIST, CIFAR10, Shakespeare), supports TensorFlow/PyTorch, and has extensions for adversarial attacks, anomaly detection, and decision trees.
    Downloads: 0 This Week
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  • 3
    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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  • 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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  • AI-powered conversation intelligence software Icon
    AI-powered conversation intelligence software

    Unlock call analytics that provide actionable insights with our call tracking software, empowering you to identify what's working and what's not.

    Every customer interaction is vital to your business success and revenue growth. With Jiminny’s AI-powered conversation intelligence software, we take recording, capturing, and meticulous analysis of call recordings to the next level. Unlock call analytics that provide actionable insights with our call tracking software, empowering you to identify what's working and what's not. Seamlessly support your biggest objectives across the entire business landscape with our innovative call tracking system.
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  • 5
    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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  • 6
    Awesome-FL

    Awesome-FL

    Comprehensive and timely academic information on federated learning

    A “awesome” curated list of federated learning (FL) academic resources: research papers, tools, frameworks, datasets, tutorials, and workshops. A hub for FL knowledge maintained by the academic community.
    Downloads: 0 This Week
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  • 7
    FL4Health

    FL4Health

    Library to facilitate federated learning research

    FL4Health is a Vector Institute toolkit for building modular, clinically-focused FL pipelines. Tailored for healthcare, it supports privacy-preserving FL, heterogeneous data settings, integrated reporting, and clear API design.
    Downloads: 0 This Week
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  • 8
    Xfl

    Xfl

    An Efficient and Easy-to-use Federated Learning Framework

    XFL is a lightweight, high-performance federated learning framework supporting both horizontal and vertical FL. It integrates homomorphic encryption, DP, secure MPC, and optimizes network resilience. Compatible with major ML libraries and deployable via Docker or Conda.
    Downloads: 0 This Week
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  • 9
    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: 2 This Week
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  • Easy-to-use Business Software for the Waste Management Software Industry Icon
    Easy-to-use Business Software for the Waste Management Software Industry

    Increase efficiency, expedite accounts receivables, optimize routes, acquire new customers, & more!

    DOP Software’s mission is to streamline waste and recycling business’ processes by providing them with dynamic, comprehensive software and services that increase productivity and quality of performance.
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  • 10
    Flower

    Flower

    Flower: A Friendly Federated Learning Framework

    A unified approach to federated learning, analytics, and evaluation. Federate any workload, any ML framework, and any programming language. Federated learning systems vary wildly from one use case to another. Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new...
    Downloads: 0 This Week
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  • 11
    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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  • 12
    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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  • 13
    FedLab

    FedLab

    A flexible Federated Learning Framework based on PyTorch

    A Python-based framework for federated learning simulation, emphasizing modularity, communication efficiency, and algorithmic flexibility. Supports both server- and client-side customization for research and development purposes.
    Downloads: 0 This Week
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  • 14
    Fedhf

    Fedhf

    A Flexible Federated Learning Simulator

    FedHF is a Python-based simulator for flexible, heterogeneous, and asynchronous federated learning research. It provides configurable resource models, supports asynchronous protocols, and accelerates experimentation.
    Downloads: 0 This Week
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