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-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 - 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 - 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-custom-game-backend-hosting-on-aws Public
The AWS Game Backend Framework allows you to integrate your game clients with AWS backend services, with secure scalable identity management and authentication, and integrations to commonly used game platform identity providers and game engines.
aws-solutions-library-samples/guidance-for-custom-game-backend-hosting-on-aws’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 - guidance-for-low-cost-semantic-search-on-aws Public
This project demonstrates how to build a cost-effective Retrieval-Augmented Generation (RAG) solution using Amazon DynamoDB as a vector store for small use cases, enabling small businesses to implement AI personalization without the high costs typically associated with specialized vector databases.
aws-solutions-library-samples/guidance-for-low-cost-semantic-search-on-aws’s past year of commit activity - guidance-for-investment-analysis-using-amazon-bedrock Public
This Guidance demonstrates how Amazon Bedrock, with offers a range of large language models (LLMs), can perform generative AI-powered analysis on structured and unstructured data sets to support investment analysts.
aws-solutions-library-samples/guidance-for-investment-analysis-using-amazon-bedrock’s past year of commit activity - guidance-for-deploying-model-context-protocol-servers-on-aws Public
This Guidance demonstrates how to securely run Model Context Protocol (MCP) servers on the AWS Cloud using containerized architecture. It helps organizations implement industry-standard OAuth 2.0 authentication while protecting server deployments with multiple security layers, including content delivery networks and web application firewalls.
aws-solutions-library-samples/guidance-for-deploying-model-context-protocol-servers-on-aws’s past year of commit activity - 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 - 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
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