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  1. guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker Public

    DeepRacer 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

    Jupyter Notebook 1.3k 706

  2. video-on-demand-on-aws video-on-demand-on-aws Public

    An automated reference implementation leveraging AWS Step Functions and AWS Media Services to deploy a scalable fault tolerant Video on demand workflow

    JavaScript 516 241

  3. cloud-intelligence-dashboards-framework cloud-intelligence-dashboards-framework Public

    Command Line Interface tool for Cloud Intelligence Dashboards deployment

    Python 503 219

  4. data-lakes-on-aws data-lakes-on-aws Public

    Enterprise-grade, production-hardened, serverless data lake on AWS

    Python 474 151

  5. fraud-detection-using-machine-learning fraud-detection-using-machine-learning Public

    Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

    Jupyter Notebook 329 164

  6. guidance-for-personalized-ecommerce-recommendations-using-amazon-bedrock-agents guidance-for-personalized-ecommerce-recommendations-using-amazon-bedrock-agents Public

    This Guidance demonstrates how to implement personalized ecommerce recommendations using Amazon Bedrock Agents.

    Python 225 11

Repositories

Showing 10 of 302 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
    Python 22 MIT-0 8 1 2 Updated Dec 30, 2025
  • aws-batch-arch-for-protein-folding Public
    aws-solutions-library-samples/aws-batch-arch-for-protein-folding’s past year of commit activity
    C++ 79 Apache-2.0 29 15 7 Updated Dec 29, 2025
  • 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
    Jupyter Notebook 164 MIT-0 53 6 2 Updated Dec 24, 2025
  • 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
    JavaScript 5 MIT-0 13 0 12 Updated Dec 23, 2025
  • 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
    Python 503 MIT-0 219 26 10 Updated Dec 23, 2025
  • 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
    TypeScript 16 MIT-0 3 0 3 Updated Dec 22, 2025
  • 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
    Java 3 Apache-2.0 0 0 1 Updated Dec 19, 2025
  • 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
    HCL 39 MIT-0 11 0 3 Updated Dec 19, 2025
  • 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
    Python 2 MIT-0 2 0 8 Updated Dec 19, 2025
  • 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
    Python 27 MIT 5 0 0 Updated Dec 18, 2025
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