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Get hands-on with deep learning

Learn the basics of deep learning - a machine learning technique that uses neural networks to learn and make predictions - through computer vision projects, tutorials, and real world, hands-on exploration with a physical device. AWS DeepLens lets you run deep learning models locally on the camera to analyze and take action on what it sees.

Andy Jassy Announcing AWS DeepLens

AWS DeepLens Demo by Dr. Matt Wood

A new way to learn machine learning

AWS DeepLens allows developers of all skill levels to get started with deep learning in less than 10 minutes by providing sample projects with practical, hands-on examples which can start running with a single click.

Custom built for deep learning

AWS DeepLens was designed with deep learning in mind. With over 100 GFLOPS of compute power on the device, it can process deep learning predictions on HD video for real time.

Build custom models with Amazon SageMaker

Models trained in Amazon SageMaker can be sent to AWS DeepLens with just a few clicks from the AWS Management Console.

Broad framework support

AWS developers can run any deep learning framework, including TensorFlow and Caffe. AWS DeepLens comes pre-installed with a high performance, efficient, optimized inference engine for deep learning using Apache MXNet.

Integrated with AWS

AWS DeepLens can stream video back to AWS using Amazon Kinesis Video Streams, and apply more advanced video analytics using Amazon Rekognition Video. The device also connects securely to AWS IoT, Amazon SQS, Amazon SNS, Amazon S3, Amazon DynamoDB, and more.

Fully programmable

AWS DeepLens is easy to customize and is fully programmable using AWS Lambda. The deep learning models in DeepLens even run as part of an AWS Lambda function, providing a familiar programming environment to experiment with.

10 minutes to your first deep learning project

Choose your deep learning model from the AWS DeepLens pre-trained model library, or your own models trained with Amazon SageMaker.

Deploy your model to the device with a single click.

Watch the results in real time in the AWS Management Console.

Sample Projects

You can build custom deep learning models in the cloud using Amazon SageMaker, or use the collection of pre-trained models included with AWS DeepLens.