Organizacja tensorflow na GitHubie posiada szeroki zakres publicznych repozytoriów, które koncentrują się na uczeniu maszynowym. Najważniejsze z nich to tensorflow, models oraz tfjs, które wykorzystują języki programowania takie jak Python, TypeScript oraz C++. Repozytoria te są kluczowe dla społeczności zajmującej się badaniami w dziedzinie uczenia głębokiego.
An Open Source Machine Learning Framework for Everyone
Models and examples built with TensorFlow
A WebGL accelerated JavaScript library for training and deploying ML models.
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Pretrained models for TensorFlow.js
Play with neural networks!
WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.
TensorFlow examples
TensorFlow's Visualization Toolkit
Examples built with TensorFlow.js
TensorFlow Neural Machine Translation Tutorial
A flexible, high-performance serving system for machine learning models
TensorFlow documentation
Swift for TensorFlow
Rust language bindings for TensorFlow
Reference models and tools for Cloud TPUs.
A collection of infrastructure and tools for research in neural network interpretability.
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
Probabilistic reasoning and statistical analysis in TensorFlow
An open-source implementation of the AlphaGoZero algorithm
A library for transfer learning by reusing parts of TensorFlow models.
Fast and flexible AutoML with learning guarantees.
Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).
Lingvo
TensorFlow Graphics: Differentiable Graphics Layers for TensorFlow
Learning to Rank in TensorFlow
TFX is an end-to-end platform for deploying production ML pipelines
An open-source Python framework for hybrid quantum-classical machine learning.
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
Library for training machine learning models with privacy for training data
Deep learning with dynamic computation graphs in TensorFlow
"Multi-Level Intermediate Representation" Compiler Infrastructure
Useful extra functionality for TensorFlow 2.x maintained by SIG-addons
Mesh TensorFlow: Model Parallelism Made Easier
Haskell bindings for TensorFlow
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
A few exercises for use at events.
Integration of TensorFlow with other open-source frameworks
Making text a first-class citizen in TensorFlow.
Stores documents used by the TensorFlow developer community
Model analysis tools for TensorFlow
A benchmark framework for Tensorflow
TensorFlow powered JavaScript library for training and deploying ML models on Node.js.
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
Training neural models with structured signals.
Input pipeline framework
Tooling for GANs in TensorFlow
Java bindings for TensorFlow
Data compression in TensorFlow
Swift for TensorFlow Deep Learning Library
Experiments towards neural network theorem proving
Library for exploring and validating machine learning data
Translations of TensorFlow documentation
A performant and modular runtime for TensorFlow
TensorFlow/TensorRT integration
Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO
Convert TensorFlow SavedModel and Keras models to TensorFlow.js
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
Code for the TCAV ML interpretability project
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Models and examples built with Swift for TensorFlow
Additional utils and helpers to extend TensorFlow when build recommendation systems, contributed and maintained by SIG Recommenders.
WeChat Mini-program plugin for TensorFlow.js
Lattice methods in TensorFlow
A toolkit that streamlines and automates the generation of model cards
TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile / ioT devices.
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Guide for building custom op for TensorFlow
⛔️ DEPRECATED - The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud.
A set of utilities for in browser visualization with TensorFlow.js
Tensorflow's Fairness Evaluation and Visualization Toolkit
Optical music recognition in TensorFlow
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Build-related tools for TensorFlow
TensorFlow Estimator
TensorFlow.js high-level layers API
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An implementation of KFAC for TensorFlow
TensorFlow-nGraph bridge
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[Deprecated] The TensorFlow Profiler (TFProf) UI provides a visual interface for profiling TensorFlow models.
Developers helping developers. TFX-Addons is a collection of community projects to build new components, examples, libraries, and tools for TFX. The projects are organized under the auspices of the special interest group, SIG TFX-Addons. Join the group at http://goo.gle/tfx-addons-group
Utilities for passing TensorFlow-related metadata between tools
Enhanced networking support for TensorFlow. Maintained by SIG-networking.
Models in Java
WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.
Simple APIs to load and prepare data for use in machine learning models
Common code for TFX
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Model Remediation is a library that provides solutions for machine learning practitioners working to create and train models in a way that reduces or eliminates user harm resulting from underlying performance biases.
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Bazel toolchain configurations used across TensorFlow ecosystem
Using DTensor on Google Cloud
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tensorflow buduje szereg projektów związanych z uczeniem maszynowym, w tym framework tensorflow oraz zestawy modeli w repozytorium models. Te repozytoria dostarczają narzędzi do tworzenia i wdrażania modeli ML.
Organizacja tensorflow korzysta głównie z języków programowania takich jak Python, TypeScript, C++, Jupyter Notebook, Java i Swift. Te języki są używane w różnych repozytoriach, aby umożliwić rozwój technologii ML.
Tak, wszystkie repozytoria tensorflow są publiczne. Umożliwia to społeczności dostęp do kodu źródłowego oraz przykładów, co sprzyja współpracy i innowacjom w dziedzinie uczenia maszynowego.
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