TensorFlow 2 focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs, and flexible model building on any platform.
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Essential documentation
Install TensorFlow
Install the package or build from source. GPU support for CUDA®-enabled cards.Migrate to TensorFlow 2
Learn how to migrate your TF1.x code to TF2.Keras
Keras is a high-level API that's easier for ML beginners, as well as researchers.TensorFlow basics
Learn about the fundamental classes and features that make TensorFlow work.Data input pipelines
Thetf.data API enables you to build complex input pipelines from simple, reusable pieces.
TensorFlow 2 best practices
Learn about the best practices for effective development using TensorFlow 2.Save a model
Save a TensorFlow model using checkpoints or the SavedModel format.Accelerators
Distribute training across multiple GPUs, multiple machines or TPUs.Performance
Best practices and optimization techniques for optimal TensorFlow performance.Libraries and extensions
Explore additional resources to build advanced models or methods using TensorFlow, and access domain-specific application packages that extend TensorFlow.-
TensorFlow Decision Forests
A library to train, run and interpret decision forest models (e.g., Random Forests, Gradient Boosted Trees) in TensorFlow. -
TensorFlow Hub
A library for the publication, discovery, and consumption of reusable parts of machine learning models. -
Serving
A TFX serving system for ML models, designed for high-performance in production environments. -
TensorFlow Federated
A framework for machine learning and other computations on decentralized data. -
Neural Structured Learning
A learning paradigm to train neural networks by leveraging structured signals in addition to feature inputs. -
TensorFlow Graphics
A library of computer graphics functionalities ranging from cameras, lights, and materials to renderers. -
SIG Addons
Extra functionality for TensorFlow, maintained by SIG Addons.
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TensorBoard
A suite of visualization tools to understand, debug, and optimize TensorFlow programs. -
Datasets
A collection of datasets ready to use with TensorFlow. -
Model Optimization
The TensorFlow Model Optimization Toolkit is a suite of tools for optimizing ML models for deployment and execution. -
Probability
TensorFlow Probability is a library for probabilistic reasoning and statistical analysis. -
MLIR
MLIR unifies the infrastructure for high-performance ML models in TensorFlow. -
XLA
A domain-specific compiler for linear algebra that accelerates TensorFlow models with potentially no source code changes. -
SIG IO
Dataset, streaming, and file system extensions, maintained by SIG IO.