The Internet of Things on AWS – Official Blog
Tag: local machine learning
Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 3 of 3: Deploying to the edge
Post by Angela Wang and Tanner McRae, Senior Engineers on the AWS Solutions Architecture R&D and Innovation team This post is the third in a series on how to build and deploy a custom object detection model to the edge using Amazon SageMaker and AWS IoT Greengrass. In the previous 2 parts of the series, we walked […]
Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 1 of 3: Preparing training data
Post by Angela Wang and Tanner McRae, Engineers on the AWS Solutions Architecture R&D and Innovation team Running computer vision algorithms at the edge unlocks many industry use cases that has low or limited internet connectivity. Combining services from AWS in the Machine Learning (ML) and Internet of Things (IoT) space, training a custom computer vision model and running […]
Using AWS IoT for Predictive Maintenance
The interest in machine learning for industrial and manufacturing use cases on the edge is growing. Manufacturers need to know when a machine is about to fail so they can better plan for maintenance. For example, as a manufacturer, you might have a machine that is sensitive to various temperature, velocity, or pressure changes. When […]
Using Chainer Neural Network Framework with AWS Greengrass ML Inference
Starting today, Greengrass ML inference includes a pre-built Chainer package for all devices powered by Intel Atom, NVIDIA Jetson TX2, and Raspberry Pi. So, you don’t have to build and configure the ML framework for your devices from scratch. With this launch, we now provide pre-built packages for three popular machine learning frameworks including TensorFlow, […]