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Why TensorFlow

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.

Easy model building

Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging.

Robust ML production anywhere

Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use.

Powerful experimentation for research

A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster.

Solutions to common ML problems

Simple step-by-step walkthroughs to solve common ML problems with TensorFlow.

For beginners
Your first neural network

Train a neural network to classify images of clothing, like sneakers and shirts, in this fast-paced overview of a complete TensorFlow program.

For experts
Generative adversarial networks

Train a generative adversarial network to generate images of handwritten digits, using the Keras Subclassing API.

For experts
Neural machine translation with attention

Train a sequence-to-sequence model for Spanish to English translation using the Keras Subclassing API.

Powered by TensorFlow

A diverse community of developers, enterprises and researchers are using ML to solve challenging, real-world problems. Learn how their research and applications are being #PoweredbyTF and how you can share your story.

Explore our AI Service Partners

TensorFlow AI Service Partners offer a range of consulting and software solutions to help you innovate faster, solve smarter, and scale bigger with TensorFlow.

Connect with a TensorFlow AI Service Partner

Explore our collection of AI Service Partners who have experience helping businesses implement AI/ML and TensorFlow-based solutions.

News & announcements

Check out the TensorFlow blog for additional updates, and subscribe to our monthly TensorFlow newsletter to get the latest announcements sent directly to your inbox.

November 18, 2020
Enroll in the DeepLearning.AI TensorFlow: Advanced Techniques Specialization

Ready to expand your TensorFlow skills? Customize your model architecture and build real-world computer vision and generative deep learning applications in this 4-course Specialization on Coursera.

October 23, 2020
Share your work on the official @TensorFlow Twitter channel!

Submit your TensorFlow project for a chance to be featured on our #TFCommunitySpotlight, receive swag, and meet a member of the TensorFlow team.

June 29, 2020
Integrate Responsible AI practices into your ML workflow

TensorFlow is committed to helping make progress in the responsible development of AI by sharing a collection of resources and tools with the ML community.

March 10, 2020
Differentiate yourself with the TensorFlow Developer Certificate

Check out our TensorFlow Certificate program for practitioners to showcase their expertise in machine learning in an increasingly AI-driven global job market.

Resources and community support

We are committed to fostering an open and welcoming ML community. Join the TensorFlow community and help grow the ecosystem.

Use TensorFlow 2.2 to build a model or application with AI Principles in mind. As you build, ask questions related to fairness, privacy, and security.

TensorFlow Blog  

We post regularly to the TensorFlow Blog, with content from the TensorFlow team and the best articles from the community.

YouTube  

Our YouTube Channel focuses on machine learning and AI with TensorFlow. Explore a number of new shows, including TensorFlow Meets, Ask TensorFlow, and Coding TensorFlow.

For up-to-date news and updates from the community and the TensorFlow team, follow @tensorflow on Twitter.

TensorFlow announcements  

Join the TensorFlow announcement mailing list to learn about the latest release updates, security advisories, and other important information from the TensorFlow team.