AWS Machine Learning Blog

Tag: AWS DeepLens

Learn about ASLens – A deep learning project that uses AWS DeepLens to translate the American Sign Language alphabet to speech

Chris Coombs travelled all the way from Melbourne, Australia to attend AWS re:Invent 2017. He was delighted to be one of the lucky few to get his hands on AWS DeepLens. He put it to good use by entering the AWS DeepLens Challenge Hackathon. A man of many talents, he is a husband and father […]

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Learn about Dee: The DeepLens Educating Entertainer – The second place winner of the AWS DeepLens Challenge Hackathon

Matthew Clark is a software developer turned architect. He lives in Manchester in the north of England, and he’s soon to be the proud owner of a new kitchen. He’s also the creator of Dee – the DeepLens Educating Entertainer, which won second place in the AWS DeepLens Challenge. Dee is an example of how […]

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Learn about ReadToMe – The first place winner of the AWS DeepLens Challenge Hackathon

When Alex Schultz first heard about the AWS DeepLens workshop in Dr. Matt Wood’s keynote address at re:Invent 2017, little did he know that a few months later he would be the first place winner of the AWS DeepLens Challenge Hackathon, owe his kids $400, and be the star of a blog post on the […]

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Deploy Gluon models to AWS DeepLens using a simple Python API

by Tatsuya Arai, Eddie Calleja, Brad Kenstler, Jyothi Nookula, Sunil Mallya, and Vikram Madan | on | in AWS DeepLens, SageMaker | Permalink | Comments |  Share

Today we are excited to announce that you can deploy your custom models trained using Gluon to your AWS DeepLens. Gluon is an open source deep learning interface which allows developers of all skill levels to prototype, build, train, and deploy sophisticated machine learning models for the cloud, devices at the edge, and mobile apps. […]

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Announcing the winners of the AWS DeepLens Challenge

At AWS re:Invent 2017 we announced the AWS DeepLens Challenge in conjunction with Intel. The AWS DeepLens Challenge gave attendees of the re:Invent DeepLens workshops an opportunity to put their skills to the test by building a machine learning (ML) project using their AWS DeepLens. The mission was to get creative with computer vision and […]

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Build your own object classification model in SageMaker and import it to DeepLens

We are excited to launch a new feature for AWS DeepLens that allows you to import models trained using Amazon SageMaker directly into the AWS DeepLens console with one click. This feature is available as of AWS DeepLens software version 1.2.3. You can update your AWS DeepLens software by re-booting your device or by using […]

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Dive Deep into AWS DeepLens Lambda Functions and the New Model Optimizer

by Jyothi Nookula and Eddie Calleja | on | in AWS DeepLens | Permalink | Comments |  Share

Today we launched a new Model Optimizer for AWS DeepLens, which will optimize your deep learning models to run on the DeepLens GPU efficiently, with a single line of Python. The Model Optimizer is available in AWS DeepLens software version 1.2.0. To access the GPU for inference, AWS DeepLens uses the Cl-DNN, Compute Library for […]

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AWS DeepLens Extensions: Build Your Own Project

AWS DeepLens provides a great opportunity to learn new technologies, such as deep learning and Internet of Things (IoT), as well as to build innovative systems that can solve real-world problems. The device and service comes with a set of predefined projects that make it easy to hit the ground running. It is designed as […]

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