AWS Machine Learning Blog

Category: Internet of Things

Building a lawn monitor and weed detection solution with AWS machine learning and IoT services

For new home buyers, a common challenge is to understand how to manage their lawn needs effectively. Now imagine if you’re a farmer and have to do this for many acres of land. As a farmer, some of the challenges you’d typically face include the when (when is the right time to water), the where […]

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Building a trash sorter with AWS DeepLens

In this blog post, we show you how to build a prototype trash sorter using AWS DeepLens, the AWS deep learning-enabled video camera designed for developers to learn machine learning in a fun, hands-on way. This prototype trash sorter project teaches you how to train image classification models with custom data. Image classification is a […]

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Parallelizing across multiple CPU/GPUs to speed up deep learning inference at the edge

AWS customers often choose to run machine learning (ML) inferences at the edge to minimize latency. In many of these situations, ML predictions must be run on a large number of inputs independently.  For example, running an object detection model on each frame of a video. In these cases, parallelizing ML inferences across all available CPU/GPUs […]

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Enabling healthcare access from home: Electronic Caregiver’s AWS-powered virtual caregiver  

When Electronic Caregiver’s founder and CEO, Anthony Dohrmann, started the company a decade ago, he was reacting to a difficult situation faced by 100 million Americans and countless individuals globally: the challenge of managing health treatment for chronic diseases. “Patients are often confused about their care instructions and non-adherence with care plans and medications schedules […]

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Segmenting brain tissue using Apache MXNet with Amazon SageMaker and AWS Greengrass ML Inference – Part 2

In Part 1 of this blog post, we demonstrated how to train and deploy neural networks to automatically segment brain tissue from an MRI scan in a simple, streamlined way using Amazon SageMaker. We used Apache MXNet to train a convolutional neural network (CNN) on Amazon SageMaker using the Bring Your Own Script paradigm. We […]

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Segmenting brain tissue using Apache MXNet with Amazon SageMaker and AWS Greengrass ML Inference – Part 1

Annotation and segmentation of medical images is a laborious endeavor that can be automated in part via deep learning (DL) techniques. These approaches have achieved state-of-the-art results in generic segmentation tasks, the goal of which is to classify images at the pixel level. In Part 1 of this blog post, we demonstrate how to train […]

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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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