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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 1.2k 714

  2. 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 294 156

  3. guidance-for-media2cloud-on-aws guidance-for-media2cloud-on-aws Public

    Guidance 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 …

    JavaScript 114 64

  4. aws-ops-automator aws-ops-automator Public archive

    A solution for automated and scheduled execution of actions on selected AWS resources, including an updated EBS Snapshot Scheduler

    Python 101 47

  5. guidance-for-modernizing-electric-vehicle-charging-on-aws guidance-for-modernizing-electric-vehicle-charging-on-aws Public

    This guidance demonstrates how the OCPP Gateway acts as a proxy between OCPP and MQTT, enabling integration with AWS IoT Core and downstream CPO services built on AWS.

    TypeScript 74 27

  6. aws-batch-arch-for-protein-folding aws-batch-arch-for-protein-folding Public

    Python 72 27

Repositories

Showing 10 of 186 repositories
  • guidance-for-amazon-vpc-lattice-automated-dns-configuration-on-aws Public

    This guidance automates the creation of DNS resolution configuration in Amazon Route 53 when creating new Amazon VPC Lattice services with custom domain names.

    aws-solutions-library-samples/guidance-for-amazon-vpc-lattice-automated-dns-configuration-on-aws’s past year of commit activity
    HCL 1 MIT-0 0 0 0 Updated Nov 9, 2024
  • guidance-automated-insight-extraction-framework-for-customer-feedback-analysis-with-amazon-bedrock Public

    This Guidance demonstrates how to streamline the process of extracting insights from customer feedback, enabling businesses to make data-driven decisions and enhance the overall customer experience.

    aws-solutions-library-samples/guidance-automated-insight-extraction-framework-for-customer-feedback-analysis-with-amazon-bedrock’s past year of commit activity
    Python 4 MIT-0 1 0 0 Updated Nov 8, 2024
  • guidance-for-custom-search-of-an-enterprise-knowledge-base-with-amazon-opensearch-service Public

    This Guidance demonstrates how to build an application for search based on the information in an enterprise knowledge base through the deployment of interface nodes, including large language models (LLMs).

    aws-solutions-library-samples/guidance-for-custom-search-of-an-enterprise-knowledge-base-with-amazon-opensearch-service’s past year of commit activity
    Python 8 MIT-0 3 2 9 Updated Nov 7, 2024
  • 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
    JavaScript 16 MIT-0 12 20 (3 issues need help) 1 Updated Nov 7, 2024
  • 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

    aws-solutions-library-samples/guidance-for-machine-learning-inference-on-aws’s past year of commit activity
    Shell 39 MIT-0 9 5 2 Updated Nov 6, 2024
  • 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 20 MIT-0 6 2 1 Updated Nov 6, 2024
  • guidance-for-developing-apple-ios-and-vision-pro-applications-with-unity-on-amazon-ec2 Public

    This Guidance demonstrates how developers can build applications on mobile iOS and Apple Vision Pro in the AWS Cloud using Unity—a widely-used game engine and development platform where developers can create immersive 2D and 3D interactive experiences.

    aws-solutions-library-samples/guidance-for-developing-apple-ios-and-vision-pro-applications-with-unity-on-amazon-ec2’s past year of commit activity
    TypeScript 26 MIT-0 4 0 0 Updated Nov 5, 2024
  • guidance-for-automating-sap-configuration-health-checks-on-aws Public

    This Guidance shows how to automate evaluation of your SAP landscape on AWS against 100+ health checks and architecture best practices aligned with the AWS Well-Architected Framework.

    aws-solutions-library-samples/guidance-for-automating-sap-configuration-health-checks-on-aws’s past year of commit activity
    3 MIT-0 2 0 0 Updated Nov 4, 2024
  • guidance-for-modernizing-electric-vehicle-charging-on-aws Public

    This guidance demonstrates how the OCPP Gateway acts as a proxy between OCPP and MQTT, enabling integration with AWS IoT Core and downstream CPO services built on AWS.

    aws-solutions-library-samples/guidance-for-modernizing-electric-vehicle-charging-on-aws’s past year of commit activity
    TypeScript 74 MIT-0 27 4 8 Updated Nov 4, 2024
  • 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 12 MIT-0 2 0 0 Updated Nov 1, 2024

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