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tensorflow avatar

tensorflow/federated

0
View on GitHub↗
2,441 stars·604 forks·Python·Apache-2.0·14 views

Federated

An open-source framework for machine learning and other computations on decentralized data.

Features

  • Federated Learning - Framework for implementing federated learning algorithms.
  • Machine Learning Frameworks - Framework for machine learning on decentralized data.
  • Perception and Machine Learning - Framework for machine learning on decentralized data.

Star history

Star history chart for tensorflow/federatedStar history chart for tensorflow/federated

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Federated

These projects share indexed features with Federated. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • autowarefoundation/modelzooautowarefoundation avatar

    autowarefoundation/modelzoo

    63View on GitHub↗

    A collection of machine-learned models for use in autonomous driving applications.

    Python
    View on GitHub↗63
  • catalyst-team/catalystcatalyst-team avatar

    catalyst-team/catalyst

    3,376View on GitHub↗

    Accelerated deep learning R&D

    Python
    View on GitHub↗3,376
  • alibaba/mnnalibaba avatar

    alibaba/MNN

    14,242View on GitHub↗

    MNN is a high-performance inference engine and framework designed for on-device machine learning. It provides a comprehensive environment for executing, optimizing, and deploying neural network models directly on mobile and resource-constrained edge devices. The framework distinguishes itself through a robust model optimization toolkit that supports quantization, compression, and structural graph manipulation to minimize memory footprint and maximize execution speed. It features a modular architecture that abstracts hardware-specific backends, allowing models to run efficiently across diverse

    C++armconvolutiondeep-learning
    View on GitHub↗14,242
  • davisking/dlibdavisking avatar

    davisking/dlib

    14,399View on GitHub↗

    dlib is a C++ machine learning toolkit and data analysis framework. It provides a collection of algorithms and utilities for building predictive modeling applications and performing statistical analysis on large datasets within native C++ environments. The project functions as a binding library that wraps low-level C++ machine learning algorithms into high-level Python scripting interfaces. This allows for the integration of high-performance native implementations with Python for machine learning development. The framework covers the implementation of predictive models, the execution of mach

    C++c-plus-pluscomputer-visiondeep-learning
    View on GitHub↗14,399
Compare all 30 related projects→

Frequently asked questions

What does tensorflow/federated do?

An open-source framework for machine learning and other computations on decentralized data.

What are the main features of tensorflow/federated?

The main features of tensorflow/federated are: Federated Learning, Machine Learning Frameworks, Perception and Machine Learning.

Which projects share features with tensorflow/federated?

Projects with overlapping indexed features include: catalyst-team/catalyst — Accelerated deep learning R&D. deap/deap. alibaba/mnn — MNN is a high-performance inference engine and framework designed for on-device machine learning. It provides a… autowarefoundation/modelzoo — A collection of machine-learned models for use in autonomous driving applications. davisking/dlib — dlib is a C++ machine learning toolkit and data analysis framework. It provides a collection of algorithms and… epistasislab/tpot — TPOT is a Python automated machine learning tool and pipeline framework. It automatically searches, selects, and tunes…