Why TensorFlow
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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.
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Simple step-by-step walkthroughs to solve common ML problems with TensorFlow.
Train a neural network to classify images of clothing, like sneakers and shirts, in this fast-paced overview of a complete TensorFlow program.
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Train a sequence-to-sequence model for Spanish to English translation using the Keras Subclassing API.
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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.
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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.
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.
The Machine Learning Crash Course is a self-study guide for aspiring machine learning practitioners featuring a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.
Our virtual Dev Summit brought announcements of TensorFlow 2.2 plus many new features and additions to the ecosystem! Read the recap on our blog to learn about the updates and watch video recordings of every session.
Check out our TensorFlow Certificate program for practitioners to showcase their expertise in machine learning in an increasingly AI-driven global job market.
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We are committed to fostering an open and welcoming ML community. Join the TensorFlow community and help grow the ecosystem.
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For up-to-date news and updates from the community and the TensorFlow team, follow @tensorflow on Twitter.
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