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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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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guidance-for-personalized-ecommerce-recommendations-using-amazon-bedrock-agents
guidance-for-personalized-ecommerce-recommendations-using-amazon-bedrock-agents PublicThis Guidance demonstrates how to implement personalized ecommerce recommendations using Amazon Bedrock Agents.
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guidance-for-multi-provider-generative-ai-gateway-on-aws
guidance-for-multi-provider-generative-ai-gateway-on-aws PublicThis Guidance demonstrates how to streamline access to numerous large language models (LLMs) through a unified, industry-standard API gateway based on OpenAI API standards
Repositories
- guidance-for-medialake-on-aws Public
This Guidance demonstrates how to deploy a media lake, which addresses media management challenges for organizations of all sizes using AWS services and partner integrations.
aws-solutions-library-samples/guidance-for-medialake-on-aws’s past year of commit activity - guidance-for-generative-ai-assistant-on-aws Public
This Guidance shows how to unlock instant insights with a generative AI assistant that transforms content consumption across diverse sources, including web documents, PDFs, media files, and YouTube videos.
aws-solutions-library-samples/guidance-for-generative-ai-assistant-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 - 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 - accelerated-intelligent-document-processing-on-aws Public
This Guidance demonstrates 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-a-predictive-responsible-gaming-model-using-amazon-sagemaker Public
This Guidance shows how you can build and train an ML model using Amazon SageMaker AI to predict problematic gambling behavior.
aws-solutions-library-samples/guidance-for-a-predictive-responsible-gaming-model-using-amazon-sagemaker’s past year of commit activity - guidance-for-developing-data-and-ai-foundation-with-amazon-sagemaker Public
DAIVI is a reference solution with IAC modules to accelerate development of Data, Analytics, AI and Visualization applications on AWS using the next generation Amazon SageMaker Unified Studio. The goal of the DAIVI solution is to provide engineers with sample infrastructure-as-code modules and application modules to build their data platforms.
aws-solutions-library-samples/guidance-for-developing-data-and-ai-foundation-with-amazon-sagemaker’s past year of commit activity - guidance-for-workforce-management-using-amazon-bedrock Public
This Guidance shows how to enhance workforce management through AI-driven automation and real-time intelligence. It demonstrates how to provide staff with quick access to relevant insights, enabling more informed decision-making
aws-solutions-library-samples/guidance-for-workforce-management-using-amazon-bedrock’s past year of commit activity - guidance-for-vibe-coding-with-aws-mcp-servers Public
Hands-on guidance for AI-accelerated AWS development using AWS MCP Servers. Learn to leverage AI coding assistants to enhance your development workflows with AWS best practices.
aws-solutions-library-samples/guidance-for-vibe-coding-with-aws-mcp-servers’s past year of commit activity - guidance-for-disaster-recovery-of-vmware-workloads-using-aws-elastic-disaster-recovery-service Public
This Guidance demonstrates how to implement disaster recovery for VMware workloads to AWS using AWS Elastic Disaster Recovery (AWS DRS). It helps organizations establish continuous replication and automated failover capabilities for both on-premises VMware environments and Amazon Elastic VMware Service (EVS).
aws-solutions-library-samples/guidance-for-disaster-recovery-of-vmware-workloads-using-aws-elastic-disaster-recovery-service’s past year of commit activity
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