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book_path: /overview/_book.yaml
project_path: /overview/_project.yaml
title: Guide
landing_page:
custom_css_path: /site-assets/css/style.css
nav: left
meta_tags:
- name: description
content: >
Learn basic and advanced concepts of TensorFlow such as eager execution, Keras
high-level APIs and flexible model building.
rows:
- classname:
devsite-landing-row-100
devsite-landing-row-large-headings
items:
- description: >
<p>
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.
</p>
<p>
Many guides are written as Jupyter notebooks and run directly in
Google Colab—a hosted notebook environment that requires no setup.
Click the <em>Run in Google Colab</em> button.
</p>
- heading: Essential documentation
classname: tfo-landing-page-heading
items:
- classname: tfo-landing-page-card
description: >
<a href="/install"><h3 class="no-link">Install TensorFlow</h3></a>
Install the package or build from source. GPU support for
CUDA®-enabled cards.
path: /install
- classname: tfo-landing-page-card
description: >
<a href="/guide/migrate"><h3 class="no-link">Migrate to TensorFlow 2</h3></a>
Learn how to migrate your TF1.x code to TF2.
path: /guide/migrate
- classname: tfo-landing-page-card
description: >
<a href="/guide/keras/overview"><h3 class="no-link">Keras</h3></a>
Keras is a high-level API that's easier for ML beginners, as well as
researchers.
path: /guide/keras/overview
- items:
- classname: tfo-landing-page-card
description: >
<a href="/guide/eager"><h3 class="no-link">TensorFlow basics</h3></a>
Learn about the fundamental classes and features that make TensorFlow
work.
path: /guide/eager
- classname: tfo-landing-page-card
description: >
<a href="/guide/data"><h3 class="no-link">Data input pipelines</h3></a>
The <code>tf.data</code> API enables you to build complex input pipelines
from simple, reusable pieces.
path: /guide/data
- classname: tfo-landing-page-card
description: >
<a href="/guide/effective_tf2"><h3 class="no-link">TensorFlow 2 best practices</h3></a>
Learn about the best practices for effective development using TensorFlow 2.
path: /guide/effective_tf2
- items:
- classname: tfo-landing-page-card
description: >
<a href="/guide/checkpoint"><h3 class="no-link">Save a model</h3></a>
Save a TensorFlow model using checkpoints or the SavedModel format.
path: /guide/checkpoint
- classname: tfo-landing-page-card
description: >
<a href="/guide/distributed_training"><h3 class="no-link">Accelerators</h3></a>
Distribute training across multiple GPUs, multiple machines or TPUs.
path: /guide/distributed_training
- classname: tfo-landing-page-card
description: >
<a href="/guide/function"><h3 class="no-link">Performance</h3></a>
Best practices and optimization techniques for optimal TensorFlow performance.
path: /guide/function
- classname: devsite-landing-row-100
items:
- description: >
<h2 class="tfo-landing-page-heading no-link">Libraries and extensions</h2>
Explore <a href="/resources">additional resources</a> to build advanced
models or methods using TensorFlow, and access domain-specific
application packages that extend TensorFlow.
- classname: devsite-landing-row-100
items:
- list:
- description: >
<a href="/decision_forests"><h3 class="tfo-landing-page-heading no-link">TensorFlow Decision Forests
</h3></a>
A library to train, run and interpret decision forest models (e.g., Random Forests,
Gradient Boosted Trees) in TensorFlow.
path: /decision_forests
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/hub"><h3 class="tfo-landing-page-heading no-link">TensorFlow Hub</h3></a>
A library for the publication, discovery, and consumption of reusable
parts of machine learning models.
path: /hub
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/tfx/guide/serving"><h3 class="tfo-landing-page-heading no-link">Serving</h3></a>
A TFX serving system for ML models, designed for high-performance in
production environments.
path: /tfx/guide/serving
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/federated"><h3 class="tfo-landing-page-heading no-link">TensorFlow Federated</h3></a>
A framework for machine learning and other computations on decentralized
data.
path: /federated
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/neural_structured_learning"><h3 class="tfo-landing-page-heading no-link">Neural Structured Learning</h3></a>
A learning paradigm to train neural networks by leveraging structured
signals in addition to feature inputs.
path: /neural_structured_learning
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/graphics"><h3 class="tfo-landing-page-heading no-link">TensorFlow Graphics</h3></a>
A library of computer graphics functionalities ranging from cameras, lights, and materials to renderers.
path: /graphics
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="https://github.com/tensorflow/addons"><h3 class="tfo-landing-page-heading no-link">SIG Addons</h3></a>
Extra functionality for TensorFlow, maintained by SIG Addons.
path: https://github.com/tensorflow/addons
icon:
icon_name: chevron_right
foreground: theme
background: grey
- list:
- description: >
<a href="/tensorboard"><h3 class="tfo-landing-page-heading no-link">TensorBoard</h3></a>
A suite of visualization tools to understand, debug, and optimize
TensorFlow programs.
path: /tensorboard
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/datasets"><h3 class="tfo-landing-page-heading no-link">Datasets</h3></a>
A collection of datasets ready to use with TensorFlow.
path: /datasets
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/model_optimization"><h3 class="tfo-landing-page-heading no-link">Model Optimization</h3></a>
The TensorFlow Model Optimization Toolkit is a suite of tools for
optimizing ML models for deployment and execution.
path: /model_optimization
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/probability"><h3 class="tfo-landing-page-heading no-link">Probability</h3></a>
TensorFlow Probability is a library for probabilistic reasoning and
statistical analysis.
path: /probability
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/mlir"><h3 class="tfo-landing-page-heading no-link">MLIR</h3></a>
MLIR unifies the infrastructure for high-performance ML models in
TensorFlow.
path: /mlir
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="/xla"><h3 class="tfo-landing-page-heading no-link">XLA</h3></a>
A domain-specific compiler for linear algebra that accelerates
TensorFlow models with potentially no source code changes.
path: /xla
icon:
icon_name: chevron_right
foreground: theme
background: grey
- description: >
<a href="https://github.com/tensorflow/io"><h3 class="tfo-landing-page-heading no-link">SIG IO</h3></a>
Dataset, streaming, and file system extensions, maintained by SIG IO.
path: https://github.com/tensorflow/io
icon:
icon_name: chevron_right
foreground: theme
background: grey