aws-solutions-library-samples
Popular repositories
-
guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker
guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker PublicDeepRacer workshop content
-
guidance-for-media2cloud-on-aws
guidance-for-media2cloud-on-aws PublicGuidance for Media2Cloud on AWS solution (formerly known as AWS Media2Cloud Solution) is designed to demonstrate a serverless ingest framework that can quickly setup a baseline ingest workflow for …
-
aws-ops-automator
aws-ops-automator Public archiveA solution for automated and scheduled execution of actions on selected AWS resources, including an updated EBS Snapshot Scheduler
-
-
guidance-for-natural-language-queries-of-relational-databases-on-aws
guidance-for-natural-language-queries-of-relational-databases-on-aws PublicDemonstration of Natural Language Query (NLQ) of an Amazon RDS for PostgreSQL database, using SageMaker JumpStart, Amazon Bedrock, LangChain, Streamlit, and Chroma.
-
guidance-for-custom-search-of-an-enterprise-knowledge-base-on-aws
guidance-for-custom-search-of-an-enterprise-knowledge-base-on-aws Public
Repositories
- guidance-for-game-server-hosting-using-agones-and-open-match-on-amazon-eks Public
This guidance provides code and instructions to create a multi Kubernetes cluster environment to host a match making and game server solution, integrating Open Match, Agones and Amazon Elastic Kubernetes Service (Amazon EKS), for a session-based multiplayer game.
- guidance-for-machine-learning-inference-on-aws Public
This Guidance demonstrates how to deploy a machine learning inference architecture on Amazon Elastic Kubernetes Service (Amazon EKS). It addresses the basic implementation requirements as well as ways you can pack thousands of unique PyTorch deep learning (DL) models into a scalable architecture and evaluate performance at scale
- osml-tile-server Public
- osml-tile-server-test Public
- osml-models Public
- osml-model-runner Public
- osml-model-runner-test Public
- guidance-for-processing-overhead-imagery-on-aws Public
This Guidance demonstrates how to process remote sensing imagery using machine learning models that automatically detect and identify objects collected from satellites, unmanned aerial vehicles, and other remote sensing devices
- osml-cdk-constructs Public
- guidance-for-analytics-observability-on-aws Public
This Guidance demonstrates how you can improve the observability of your data pipelines running on Apache Spark.