ライブラリと拡張機能
TensorFlow を使用して高度なモデルやメソッドを構築するための各種ライブラリや、TensorFlow を拡張するドメイン固有のアプリケーション パッケージをご用意しています。
-
ドキュメントを表示Extra functionality for TensorFlow, maintained by SIG Addons.
TensorFlow Addons
-
ドキュメントを表示A library for designing, testing, and implementing reinforcement learning algorithms.
TensorFlow Agents
-
ドキュメントを表示A library to build ML models with end-to-end optimized data compression built in.
TensorFlow Compression
-
ドキュメントを表示A library to analyze training and serving data to compute descriptive statistics, infer schemas, and detect anomalies.
TensorFlow Data Validation
-
ドキュメントを表示State-of-the-art algorithms for training, serving and interpreting models that use decision forests for classification, regression and ranking.
TensorFlow Decision Forests
-
A research framework for fast prototyping of reinforcement learning algorithms.
Dopamine
-
ドキュメントを表示A library that enables easy computation of commonly-identified fairness metrics for binary and multiclass classifiers.
Fairness Indicators
-
ドキュメントを表示An open source framework for machine learning and other computations on decentralized data.
TensorFlow Federated
-
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 GNN
-
ドキュメントを表示A library of computer graphics functionalities ranging from cameras, lights, and materials to renderers.
TensorFlow Graphics
-
ドキュメントを表示A library for reusable machine learning. Download and reuse the latest trained models with a minimal amount of code.
TensorFlow Hub
-
ドキュメントを表示Dataset, streaming, and file system extensions, maintained by SIG IO.
TensorFlow IO
-
ドキュメントを表示Language bindings for Java and other JVM languages, such as Scala or Kotlin.
TensorFlow JVM
-
A library of modular components for common computer vision tasks such as data augmentation, classification, object detection, segmentation, and more.
KerasCV
-
An easily customizable natural language processing library providing modular components and state-of-the-art preset weights and architectures.
KerasNLP
-
ドキュメントを表示A library for flexible, controlled and interpretable ML solutions with common-sense shape constraints.
TensorFlow Lattice
-
ドキュメントを表示A library to run ML models on digital signal processors (DSPs), microcontrollers, and other devices with limited memory.
TensorFlow Lite Micro
-
ドキュメントを表示A library that simplifies model training for on-device natural language processing, vision, and audio applications.
TensorFlow Lite Model Maker
-
ドキュメントを表示A toolkit to customize model interface on Android, create metadata, and build inference pipelines for mobile deployment.
TensorFlow Lite Support
-
Utilities for passing TensorFlow-related metadata between tools.
TensorFlow Metadata
-
ドキュメントを表示A library for recording and retrieving MLOps metadata associated with machine learning workflows.
ML Metadata
-
ドキュメントを表示A library for deep analysis of model results beyond simple training metrics, to measure edge and corner cases and bias.
TensorFlow Model Analysis
-
ドキュメントを表示A collection of tools to generate documents that provide context and transparency into a model's development and performance.
Model Card Toolkit
-
ドキュメントを表示A suite of tools for optimizing ML models for deployment and execution.
Model Optimization Toolkit
-
ドキュメントを表示A library to help create and train models in a way that reduces or eliminates user harm resulting from underlying performance biases.
TensorFlow Model Remediation
-
Utilities for manipulating data in a n-dimensional space in Java, maintained by SIG JVM.
NdArray
-
ドキュメントを表示A learning framework to train neural networks by leveraging structured signals in addition to feature inputs.
Neural Structured Learning
-
ドキュメントを表示A Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy.
TensorFlow Privacy
-
ドキュメントを表示A library for probabilistic reasoning and statistical analysis.
TensorFlow Probability
-
ドキュメントを表示A quantum machine learning library for rapid prototyping of hybrid quantum-classical ML models.
TensorFlow Quantum
-
ドキュメントを表示A library for Learning-to-Rank (LTR) techniques on the TensorFlow platform.
TensorFlow Ranking
-
ドキュメントを表示A library for building recommender system models.
TensorFlow Recommenders
-
A collection of community projects introducing Dynamic Embedding Technology to large-scale recommendation systems built upon TensorFlow
TensorFlow Recommenders Addons
-
ドキュメントを表示A flexible, high-performance serving system for machine learning models, designed for production environments
TensorFlow Serving
-
A library from DeepMind for constructing neural networks.
Sonnet
-
ドキュメントを表示A collection of text- and NLP-related classes and ops ready to use with TensorFlow 2.
TensorFlow Text
-
ドキュメントを表示A library for large-scale feature engineering and eliminating training-serving skew.
TensorFlow Transform
-
ドキュメントを表示A hardware-accelerated library for training and deploying ML models using JavaScript or Node.js.
TensorFlow.js
-
ドキュメントを表示An end-to-end platform for deploying production ML pipelines.
TFX
-
ドキュメントを表示A collection of community projects to build new components, examples, libraries, and tools for TFX.
TFX-Addons