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Libraries & extensions

Explore libraries to build advanced models or methods using TensorFlow, and access domain-specific application packages that extend TensorFlow.

• TensorFlow Addons

  Extra functionality for TensorFlow, maintained by SIG Addons.

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• TensorFlow Agents

  A library for designing, testing, and implementing reinforcement learning algorithms.

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• TensorFlow Compression

  A library to build ML models with end-to-end optimized data compression built in.

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• TensorFlow Data Validation

  A library to analyze training and serving data to compute descriptive statistics, infer schemas, and detect anomalies.

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• TensorFlow Decision Forests

  State-of-the-art algorithms for training, serving and interpreting models that use decision forests for classification, regression and ranking.

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• Dopamine

  A research framework for fast prototyping of reinforcement learning algorithms.

• Fairness Indicators

  A library that enables easy computation of commonly-identified fairness metrics for binary and multiclass classifiers.

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• TensorFlow Federated

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

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• TensorFlow GNN

  A library to build neural networks on graph data (nodes and edges with arbitrary features), including tools for preparing input data and training models.

• TensorFlow Graphics

  A library of computer graphics functionalities ranging from cameras, lights, and materials to renderers.

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• TensorFlow Hub

  A library for reusable machine learning. Download and reuse the latest trained models with a minimal amount of code.

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• TensorFlow IO

  Dataset, streaming, and file system extensions, maintained by SIG IO.

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• TensorFlow JVM

  Language bindings for Java and other JVM languages, such as Scala or Kotlin.

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• KerasCV

  A library of modular components for common computer vision tasks such as data augmentation, classification, object detection, segmentation, and more.

• KerasNLP

  An easily customizable natural language processing library providing modular components and state-of-the-art preset weights and architectures.

• TensorFlow Lattice

  A library for flexible, controlled and interpretable ML solutions with common-sense shape constraints.

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• TensorFlow Lite Micro

  A library to run ML models on digital signal processors (DSPs), microcontrollers, and other devices with limited memory.

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• TensorFlow Lite Model Maker

  A library that simplifies model training for on-device natural language processing, vision, and audio applications.

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• TensorFlow Lite Support

  A toolkit to customize model interface on Android, create metadata, and build inference pipelines for mobile deployment.

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• Utilities for passing TensorFlow-related metadata between tools.

• A library for recording and retrieving MLOps metadata associated with machine learning workflows.

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• TensorFlow Model Analysis

  A library for deep analysis of model results beyond simple training metrics, to measure edge and corner cases and bias.

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• A collection of tools to generate documents that provide context and transparency into a model's development and performance.

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• A suite of tools for optimizing ML models for deployment and execution.

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• A library to help create and train models in a way that reduces or eliminates user harm resulting from underlying performance biases.

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• NdArray

  Utilities for manipulating data in a n-dimensional space in Java, maintained by SIG JVM.

• Neural Structured Learning

  A learning framework to train neural networks by leveraging structured signals in addition to feature inputs.

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• TensorFlow Privacy

  A Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy.

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• TensorFlow Probability

  A library for probabilistic reasoning and statistical analysis.

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• TensorFlow Quantum

  A quantum machine learning library for rapid prototyping of hybrid quantum-classical ML models.

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• TensorFlow Ranking

  A library for Learning-to-Rank (LTR) techniques on the TensorFlow platform.

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• TensorFlow Recommenders

  A library for building recommender system models.

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• TensorFlow Recommenders Addons

  A collection of community projects introducing Dynamic Embedding Technology to large-scale recommendation systems built upon TensorFlow

• TensorFlow Serving

  A flexible, high-performance serving system for machine learning models, designed for production environments

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• Sonnet

  A library from DeepMind for constructing neural networks.

• TensorFlow Text

  A collection of text- and NLP-related classes and ops ready to use with TensorFlow 2.

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• TensorFlow Transform

  A library for large-scale feature engineering and eliminating training-serving skew.

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• TensorFlow.js

  A hardware-accelerated library for training and deploying ML models using JavaScript or Node.js.

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• TFX

  An end-to-end platform for deploying production ML pipelines.

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• TFX-Addons

  A collection of community projects to build new components, examples, libraries, and tools for TFX.

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