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

    Command Line Interface tool for Cloud Intelligence Dashboards deployment

    Python 486 208

  3. data-lakes-on-aws data-lakes-on-aws Public

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

    Python 472 149

  4. 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 324 159

  5. 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 221 11

  6. guidance-for-multi-provider-generative-ai-gateway-on-aws guidance-for-multi-provider-generative-ai-gateway-on-aws Public

    This Guidance demonstrates how to streamline access to numerous large language models (LLMs) through a unified, industry-standard API gateway based on OpenAI API standards

    HCL 169 33

Repositories

Showing 10 of 275 repositories
  • guidance-for-building-an-event-driven-sportsbook-on-aws Public

    This Guidance demonstrates how to build an event-driven, serverless sportsbook application to help sports betting operators handle spiky, seasonal traffic.

    aws-solutions-library-samples/guidance-for-building-an-event-driven-sportsbook-on-aws’s past year of commit activity
    Python 0 MIT-0 0 0 4 Updated Oct 20, 2025
  • aws-solutions-library-samples/Guidance-for-AI-enhanced-customer-experience-with-Amazon-Connect’s past year of commit activity
    7 MIT-0 2 0 0 Updated Oct 19, 2025
  • 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 18 MIT-0 7 1 2 Updated Oct 19, 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 117 MIT-0 38 11 8 Updated Oct 17, 2025
  • aws-solutions-library-samples/guidance-for-machine-translation-pipelines-using-generative-ai-on-aws’s past year of commit activity
    Python 3 MIT-0 1 0 0 Updated Oct 17, 2025
  • guidance-for-open-source-3d-reconstruction-toolbox-for-gaussian-splats-on-aws Public

    The Open Source 3D Reconstruction Toolbox for Gaussian Splats provides an end-to-end, pipeline-based guidance on AWS to reconstruct 3D scenes or objects from images or video inputs.

    aws-solutions-library-samples/guidance-for-open-source-3d-reconstruction-toolbox-for-gaussian-splats-on-aws’s past year of commit activity
    Python 39 MIT-0 1 0 0 Updated Oct 17, 2025
  • guidance-for-scalable-model-inference-and-agentic-ai-on-amazon-eks Public

    Comprehensive, scalable ML inference architecture using Amazon EKS, leveraging Graviton processors for cost-effective CPU-based inference and GPU instances for accelerated inference. Guidance provides a complete end-to-end platform for deploying LLMs with agentic AI capabilities, including RAG and MCP

    aws-solutions-library-samples/guidance-for-scalable-model-inference-and-agentic-ai-on-amazon-eks’s past year of commit activity
    Python 18 MIT-0 5 0 3 Updated Oct 17, 2025
  • guidance-for-automated-provisioning-of-application-ready-amazon-eks-clusters Public

    The EKS workload accelerator is a collection of reference implementations for Amazon EKS designed to accelerate the time it takes to provision a workload ready EKS cluster. It includes an "opinionated" set of pre-configured and integrated tools/add-ons, and best practices to support core capabilities including Autoscaling, Observability, Networking

    aws-solutions-library-samples/guidance-for-automated-provisioning-of-application-ready-amazon-eks-clusters’s past year of commit activity
    HCL 36 MIT-0 11 5 1 Updated Oct 16, 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 486 MIT-0 208 26 17 Updated Oct 16, 2025
  • guidance-for-agentic-data-exploration-on-aws Public

    This Guidance demonstrates how to overcome data fragmentation challenges by using a team of AI agents to automate the discovery, connection, and analysis of information across siloed systems.

    aws-solutions-library-samples/guidance-for-agentic-data-exploration-on-aws’s past year of commit activity
    TypeScript 3 MIT-0 2 0 0 Updated Oct 16, 2025

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