aws-solutions-library-samples
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guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker
guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker PublicDeepRacer workshop content. This Guidance demonstrates how software developers can use an Amazon SageMaker Notebook instance to directly train and evaluate AWS DeepRacer models with full control
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video-on-demand-on-aws
video-on-demand-on-aws PublicAn automated reference implementation leveraging AWS Step Functions and AWS Media Services to deploy a scalable fault tolerant Video on demand workflow
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cloud-intelligence-dashboards-framework
cloud-intelligence-dashboards-framework PublicCommand Line Interface tool for Cloud Intelligence Dashboards deployment
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data-lakes-on-aws
data-lakes-on-aws PublicEnterprise-grade, production-hardened, serverless data lake on AWS
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fraud-detection-using-machine-learning
fraud-detection-using-machine-learning PublicSetup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker
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live-streaming-on-aws
live-streaming-on-aws PublicThe live stream solution is a reference deployment that demonstrates how to deliver highly available live streaming video through an integrated workflow between Elemental Cloud and AWS.
Repositories
- guidance-for-claude-code-with-amazon-bedrock Public
This Guidance demonstrates how organizations can implement secure enterprise authentication for Amazon Bedrock using industry-standard protocols and AWS services
aws-solutions-library-samples/guidance-for-claude-code-with-amazon-bedrock’s past year of commit activity - guidance-for-game-analytics-pipeline-on-aws Public
The Game Analytics Pipeline solution helps game developers to apply a flexible, and scalable DataOps methodology to their games. Allowing them to continuously integrate, and continuously deploy a scalable serverless data pipeline for ingesting, storing, and analyzing telemetry data generated from games, and services.
aws-solutions-library-samples/guidance-for-game-analytics-pipeline-on-aws’s past year of commit activity - 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
aws-solutions-library-samples/guidance-for-processing-overhead-imagery-on-aws’s past year of commit activity - cloud-intelligence-dashboards-framework Public
Command Line Interface tool for Cloud Intelligence Dashboards deployment
aws-solutions-library-samples/cloud-intelligence-dashboards-framework’s past year of commit activity - cloud-intelligence-dashboards-data-collection Public
This Guidance demonstrates how to deploy Cloud Intelligence Dashboards in your AWS environment using AWS CloudFormation templates or command line tools. These pre-built dashboards enable you to drive financial accountability, optimize costs, and track usage goals across their AWS infrastructure.
aws-solutions-library-samples/cloud-intelligence-dashboards-data-collection’s past year of commit activity - accelerated-intelligent-document-processing-on-aws Public
The IDP Accelerator provides a scalable, serverless approach for automated document processing and information extraction using AWS services, such as Amazon Bedrock Data Automation and Amazon Bedrock foundational models. It combines generative AI and optical character recognition (OCR) to process documents at scale.
aws-solutions-library-samples/accelerated-intelligent-document-processing-on-aws’s past year of commit activity - guidance-for-developing-infrastructure-as-code-templates-from-architecture-diagrams-on-aws Public
This Guidance demonstrates how to transform architecture diagrams into Infrastructure as Code (IaC) templates using AI, addressing the challenge of time-consuming manual coding for solutions targeted for AWS deployments.
aws-solutions-library-samples/guidance-for-developing-infrastructure-as-code-templates-from-architecture-diagrams-on-aws’s past year of commit activity - guidance-for-enhancing-smart-products-through-device-telemetry-and-amazon-connect Public
This Guidance demonstrates how manufacturers can transform traditional products into intelligent, connected services using AWS IoT Core and Amazon Connect.
aws-solutions-library-samples/guidance-for-enhancing-smart-products-through-device-telemetry-and-amazon-connect’s past year of commit activity - guidance-for-aws-deepracer-event-management Public
The AWS DeepRacer Event Manager (DREM) is used to run and manage all aspects of in-person events for AWS DeepRacer, an autonomous 1/18th scale race car designed to test reinforcement learning (RL) models by racing on a physical track.
aws-solutions-library-samples/guidance-for-aws-deepracer-event-management’s past year of commit activity - guidance-for-agentic-data-analyst-using-amazon-bedrock-agentcore-on-aws Public
This guidance provides a scalable approach for deploying a Data Analyst Agent that can query hundreds of datasets hosted on Amazon Athena. Built on the Strands Agents framework and deployed on AWS AgentCore, the agent leverages semantic search powered by Amazon S3 Vectors to automatically identify and retrieve the most relevant datasets.
aws-solutions-library-samples/guidance-for-agentic-data-analyst-using-amazon-bedrock-agentcore-on-aws’s past year of commit activity
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