What technologies tensorflow.org is built with

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*   [TensorFlow](https://www.tensorflow.org/)

An end-to-end platform for machine learning

[Install TensorFlow](/install)

Get started with TensorFlow

---------------------------

TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples.

[View tutorials](/tutorials)

import tensorflow as tf

mnist \= tf.keras.datasets.mnist

(x\_train, y\_train),(x\_test, y\_test) \= mnist.load\_data()

x\_train, x\_test \= x\_train / 255.0, x\_test / 255.0

model \= tf.keras.models.Sequential(\[

  tf.keras.layers.Flatten(input\_shape\=(28, 28)),

  tf.keras.layers.Dense(128, activation\='relu'),

  tf.keras.layers.Dropout(0.2),

  tf.keras.layers.Dense(10, activation\='softmax')

\])

model.compile(optimizer\='adam',

  loss\='sparse\_categorical\_crossentropy',

  metrics\=\['accuracy'\])

model.fit(x\_train, y\_train, epochs\=5)

model.evaluate(x\_test, y\_test)

[Run quickstart](https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/quickstart/beginner.ipynb)

Solve real-world problems with ML

---------------------------------

Explore examples of how TensorFlow is used to advance research and build AI-powered applications.

TENSORFLOW.JS

Catch up on the latest from the Web AI Summit

Explore the latest advancements in running models client-side with speakers from Chrome, MediaPipe, Intel, Hugging Face, Microsoft, LangChain, and more.

[Watch now](https://www.youtube.com/watch?v=tF70o1Q8VkM&list=PLNYkxOF6rcIAEVKJ98bDkQRkwvO4grhnt)

_close_

TensorFlow GNN

[Analyze relational data using graph neural networks](https://blog.tensorflow.org/2024/02/graph-neural-networks-in-tensorflow.html)

GNNs can process complex relationships between objects, making them a powerful technique for traffic forecasting, medical discovery, and more.

[Learn about TF GNN](https://blog.tensorflow.org/2024/02/graph-neural-networks-in-tensorflow.html)

TensorFlow Agents

[Build recommendation systems with reinforcement learning](https://blog.tensorflow.org/2023/10/simulated-spotify-listening-experiences-reinforcement-learning-tensorflow-tf-agents.html)

Learn how Spotify uses the TensorFlow ecosystem to design an extendable offline simulator and train RL Agents to generate playlists.

[Read the blog](https://blog.tensorflow.org/2023/10/simulated-spotify-listening-experiences-reinforcement-learning-tensorflow-tf-agents.html)

What's new in TensorFlow

------------------------

Read the latest announcements from the TensorFlow team and community.

[](https://blog.tensorflow.org/2024/12/introducing-wake-vision-new-dataset-for-person-detection-in-tinyml.html)

[

### Introducing Wake Vision: A High-Quality, Large-Scale Dataset for TinyML Computer Vision Applications

](https://blog.tensorflow.org/2024/12/introducing-wake-vision-new-dataset-for-person-detection-in-tinyml.html)

Updated December 5, 2024

[](https://blog.tensorflow.org/2024/11/mlsysbookai-principles-and-practices-of-machine-learning-systems-engineering.html)

[

### MLSysBook.AI: Principles and Practices of Machine Learning Systems Engineering

](https://blog.tensorflow.org/2024/11/mlsysbookai-principles-and-practices-of-machine-learning-systems-engineering.html)

Updated November 19, 2024

[](https://blog.tensorflow.org/2024/10/whats-new-in-tensorflow-218.html)

[

### What's new in TensorFlow 2.18

](https://blog.tensorflow.org/2024/10/whats-new-in-tensorflow-218.html)

Updated October 28, 2024

[](https://blog.tensorflow.org/2024/07/whats-new-in-tensorflow-217.html)

[

### What's new in TensorFlow 2.17

](https://blog.tensorflow.org/2024/07/whats-new-in-tensorflow-217.html)

Updated July 18, 2024

[](https://blog.tensorflow.org/2024/04/faster-dynamically-quantized-inference-with-xnnpack.html)

[

### Faster Dynamically Quantized Inference with XNNPack

](https://blog.tensorflow.org/2024/04/faster-dynamically-quantized-inference-with-xnnpack.html)

Updated April 9, 2024

[](https://blog.tensorflow.org/2024/03/whats-new-in-tensorflow-216.html)

[

### What's new in TensorFlow 2.16

](https://blog.tensorflow.org/2024/03/whats-new-in-tensorflow-216.html)

Updated March 13, 2024

Explore the ecosystem

---------------------

Discover production-tested tools to accelerate modeling, deployment, and other workflows.

*   [

    Library

    ### TensorFlow.js

    Train and run models directly in the browser using JavaScript or Node.js.

    ](/js)

*   [

    Library

    ### LiteRT

    Deploy ML on mobile and edge devices such as Android, iOS, Raspberry Pi, and Edge TPU.

    ](https://ai.google.dev/edge/litert)

*   [

    API

    ### tf.data

    Preprocess data and create input pipelines for ML models.

    ](/guide/data)

*   [

    Library

    ### TFX

    Create production ML pipelines and implement MLOps best practices.

    ](/tfx)

*   [

    API

    ### tf.keras

    Create ML models with TensorFlow's high-level API.

    ](/guide/keras)

*   [

    Resource

    ### Kaggle Models

    Find pre-trained models ready for fine-tuning and deployment.

    ](https://www.kaggle.com/models)

*   [

    Resource

    ### TensorFlow Datasets

    Browse the collection of standard datasets for initial training and validation.

    ](/datasets)

*   [

    Tool

    ### TensorBoard

    Visualize and track development of ML models.

    ](/tensorboard)

[

### ML models & datasets

Pretrained models and ready-to-use datasets for image, text, audio, and video use cases.

](/resources/models-datasets)

[

### Libraries & extensions

Packages for domain-specific applications and APIs for languages other than Python.

](/resources/libraries-extensions)

[

### Developer tools

Tools to evaluate models, optimize performance, and productionize ML workflows.

](/resources/tools)

Join the community

Collaborate, find support, and share your projects by joining interest groups or attending developer events.

[Get involved](/community)

Learn ML

New to machine learning? Begin with TensorFlow's curated curriculums or browse the resource library of books, online courses, and videos.

[Explore resources](/resources/learn-ml)

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Start building with TensorFlow

------------------------------

[Install TensorFlow](/install) [Explore tutorials](/tutorials)
🏳️TensorFlow

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