tensorflow/tfjs-models: Pretrained models for TensorFlow.js

tensorflow/model-analysis: Model analysis tools for TensorFlow

tensorflow/sig-tfjs:

tensorflow/graphics: TensorFlow Graphics: Differentiable Graphics Layers for TensorFlow

tensorflow/autograph:

tensorflow/adanet: Fast and flexible AutoML with learning guarantees.

tensorflow/swift: Swift for TensorFlow

tensorflow/tensorboard: TensorFlow's Visualization Toolkit

tensorflow/tfx-bsl: Common code for TFX

tensorflow/tensorstore:

tensorflow/swift-apis: Swift for TensorFlow Deep Learning Library

tensorflow/rust: Rust language bindings for TensorFlow

tensorflow/tfjs-tsne:

tensorflow/nmt: TensorFlow Neural Machine Translation Tutorial

tensorflow/tfrc:

tensorflow/tflite-micro-arduino-examples:

tensorflow/java: Java bindings for TensorFlow

tensorflow/quantum: Hybrid Quantum-Classical Machine Learning in TensorFlow

tensorflow/workshops: A few exercises for use at events.

tensorflow/mlir-hlo:

tensorflow/ecosystem: Integration of TensorFlow with other open-source frameworks

tensorflow/serving: A flexible, high-performance serving system for machine learning models

tensorflow/profiler: A profiling and performance analysis tool for TensorFlow

tensorflow/federated: A framework for implementing federated learning

tensorflow/runtime: A performant and modular runtime for TensorFlow

tensorflow/swift-bindings:

tensorflow/java-ndarray:

tensorflow/tflite-support: TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile / ioT devices.

tensorflow/tfx: TFX is an end-to-end platform for deploying production ML pipelines

tensorflow/transform: Input pipeline framework

tensorflow/model-remediation: 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.

tensorflow/estimator: TensorFlow Estimator

tensorflow/ngraph-bridge: TensorFlow-nGraph bridge

tensorflow/tensorflow: An Open Source Machine Learning Framework for Everyone

tensorflow/text: Making text a first-class citizen in TensorFlow.

tensorflow/tfjs-wechat: WeChat Mini-program plugin for TensorFlow.js

tensorflow/ranking: Learning to Rank in TensorFlow

tensorflow/lingvo: Lingvo

tensorflow/docs-l10n: Translations of TensorFlow documentation

tensorflow/addons: Useful extra functionality for TensorFlow 2.x maintained by SIG-addons

tensorflow/build: Build-related tools for TensorFlow

tensorflow/decision-forests: A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

tensorflow/recommenders: TensorFlow Recommenders is a library for building recommender system models using TensorFlow.

tensorflow/tfjs-data: Simple APIs to load and prepare data for use in machine learning models

tensorflow/tensorrt: TensorFlow/TensorRT integration

tensorflow/moonlight: Optical music recognition in TensorFlow

tensorflow/mesh: Mesh TensorFlow: Model Parallelism Made Easier

tensorflow/cloud: 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.

tensorflow/neural-structured-learning: Training neural models with structured signals.

tensorflow/tflite-micro: Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).

tensorflow/tensor2tensor: Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

tensorflow/data-validation: Library for exploring and validating machine learning data

tensorflow/tpu: Reference models and tools for Cloud TPUs.

tensorflow/kfac: An implementation of KFAC for TensorFlow

tensorflow/models: Models and examples built with TensorFlow

tensorflow/lucid: A collection of infrastructure and tools for research in neural network interpretability.

tensorflow/custom-op: Guide for building custom op for TensorFlow

tensorflow/tcav: Code for the TCAV ML interpretability project

tensorflow/embedding-projector-standalone:

tensorflow/gnn: TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.

tensorflow/tfjs-converter: Convert TensorFlow SavedModel and Keras models to TensorFlow.js

tensorflow/tfjs-node: TensorFlow powered JavaScript library for training and deploying ML models on Node.js.

tensorflow/tfjs-website: WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.

tensorflow/codelabs:

tensorflow/toolchains: Bazel toolchain configurations used across TensorFlow ecosystem

tensorflow/tensorboard-plugin-example:

tensorflow/fairness-indicators: Tensorflow's Fairness Evaluation and Visualization Toolkit

tensorflow/tfjs-layers: TensorFlow.js high-level layers API

tensorflow/playground: Play with neural networks!

tensorflow/tfjs-vis: A set of utilities for in browser visualization with TensorFlow.js

tensorflow/tfjs: A WebGL accelerated JavaScript library for training and deploying ML models.

tensorflow/model-optimization: A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.

tensorflow/community: Stores documents used by the TensorFlow developer community

tensorflow/minigo: An open-source implementation of the AlphaGoZero algorithm

tensorflow/io: Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO

tensorflow/examples: TensorFlow examples

tensorflow/agents: TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

tensorflow/tfjs-models: Pretrained models for TensorFlow.js

tensorflow/recommenders-addons: Additional utils and helpers to extend TensorFlow when build recommendation systems, contributed and maintained by SIG Recommenders.

tensorflow/tfx-addons: 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

tensorflow/tfjs-core: WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.

tensorflow/model-card-toolkit: A toolkit that streamlines and automates the generation of model cards

tensorflow/probability: Probabilistic reasoning and statistical analysis in TensorFlow

tensorflow/mlir: "Multi-Level Intermediate Representation" Compiler Infrastructure

tensorflow/tfjs-examples: Examples built with TensorFlow.js

tensorflow/similarity: TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

tensorflow/gan: Tooling for GANs in TensorFlow

tensorflow/datasets: TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...

tensorflow/java-models: Models in Java

tensorflow/skflow: Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning

tensorflow/deepmath: Experiments towards neural network theorem proving

tensorflow/networking: Enhanced networking support for TensorFlow. Maintained by SIG-networking.

tensorflow/swift-models: Models and examples built with Swift for TensorFlow

tensorflow/compression: Data compression in TensorFlow

tensorflow/profiler-ui: [Deprecated] The TensorFlow Profiler (TFProf) UI provides a visual interface for profiling TensorFlow models.

tensorflow/benchmarks: A benchmark framework for Tensorflow

tensorflow/docs: TensorFlow documentation

tensorflow/metadata: Utilities for passing TensorFlow-related metadata between tools

tensorflow/haskell: Haskell bindings for TensorFlow

tensorflow/privacy: Library for training machine learning models with privacy for training data

tensorflow/hub: A library for transfer learning by reusing parts of TensorFlow models.

tensorflow/fold: Deep learning with dynamic computation graphs in TensorFlow

tensorflow/lattice: Lattice methods in TensorFlow

tensorflow/tfhub.dev: