Running multiple HPO jobs in parallel on Amazon SageMaker

By Dustin Ward

AWS FeedRunning multiple HPO jobs in parallel on Amazon SageMaker The ability to rapidly iterate and train machine learning (ML) models is key to deriving business value from ML workloads. Because ML models often have many tunable parameters (known as hyperparameters) that can influence the model’s ability to effectively learn, data scientists often use a…

How to: Build an engaging feed app with React and Amazon IVS

By Dustin Ward

AWS FeedHow to: Build an engaging feed app with React and Amazon IVS Introduction While live video streaming has become the new standard for engaging content, it is often difficult for developers with no video expertise to get started. Managing live video ingestion, processing, packaging, delivery and playback with a good user experience is a daunting…

Building a Prometheus Remote Write Exporter for the OpenTelemetry Python SDK

By Dustin Ward

AWS FeedBuilding a Prometheus Remote Write Exporter for the OpenTelemetry Python SDK In this post, AWS intern engineers Azfaar Qureshi and Shovnik Bhattacharya talk about their experience building the OpenTelemetry Prometheus Remote Write Exporter for Python. They share their experiences in tackling challenges they faced while building this tool, which is used for sending metrics…

Training and deploying models using TensorFlow 2 with the Object Detection API on Amazon SageMaker

By Dustin Ward

AWS FeedTraining and deploying models using TensorFlow 2 with the Object Detection API on Amazon SageMaker With the rapid growth of object detection techniques, several frameworks with packaged pre-trained models have been developed to provide users easy access to transfer learning. For example, GluonCV, Detectron2, and the TensorFlow Object Detection API are three popular computer…