Deep Learning with TensorFlow

Deep learning on AWS made simple

TensorFlow is one of many deep learning frameworks available to researchers and developers to enhance their applications with machine learning. AWS provides broad support for TensorFlow, enabling customers to develop and serve their own models across computer vision, natural language processing, speech translation, and more.

You can get started with TensorFlow on AWS using Amazon SageMaker, a fully managed machine learning service that makes it easy and cost-effective to build, train, and deploy TensorFlow models at scale. If you prefer to manage the infrastructure yourself, you can use the AWS Deep Learning AMIs or the AWS Deep Learning Containers, which come built from source and optimized for performance with the latest version of TensorFlow to quickly deploy custom machine learning environments.

Benefits

Visualization

TensorFlow comes with a full suite of visualization tools that make it easy to understand, debug, and optimize applications. With support for a variety of styles – from images and audio to histograms and graphs – you can train massive deep neural networks quickly and easily.

Documentation

With TensorFlow, you get access to extensive documentation and tutorials that can help accelerate your AI development. TensorFlow also has a large and extremely active community of users who regularly contribute code and resolve issues on GitHub.

Customer Testimonials

Aerobotics logo

Aerobotics, a South African agri-tech startup, provides farmers with data and intelligence through the Aeroview platform, which utilizes machine learning to extract information from aerial drone images. Using Amazon SageMaker and TensorFlow, Aerobotics was able to improve their training speed by 24 times per sample.

Read the blog »

Fannie Mae logo

Fannie Mae uses Amazon SageMaker with TensorFlow for its home appraisal model to generate accurate property valuations, which helps reduce mortgage risk.

Watch video to learn more »

Mobileeye logo

Mobileye, an Intel company, uses TensorFlow with Amazon SageMaker to develop and deliver driver assistance and autonomous vehicle solutions. Using Amazon SageMake Pipe Mode, data is streamed from Amazon S3 to training instances with the TensorFlow dataset API to allow multiple training instances to pull from the same set of decoupled training data.

Watch video to learn more »

Customers using TensorFlow on AWS

Many organizations are benefiting from the ease-of-use and flexibility of getting started using TensorFlow on AWS.
babylon logo
Georgia-Pacific logo
GoDaddy logo
Siemens logo
Propeller logo
Wix logo
zalando logo
Browsi logo
BTG logo
Cox Automotive
Thomson reuters logo
edmunds.com logo
GoodData logo
grammarly logo
Expedia logo
hudl logo
Idexx logo
intuit logo
Tradelegs logo
Matrix logo
Pinterest logo

Blogs and articles

Standard Product Icons (Features) Squid Ink
Learn how to get started with PyTorch on AWS

Visit the getting started page.

Learn more 
Sign up for a free account
Sign up for a free account

Instantly get access to the AWS Free Tier. 

Sign up 
Standard Product Icons (Start Building) Squid Ink
Start building in the console

Get started building in the AWS Management Console.

Sign in