aws-samples Goto Github PK

realtime-web-analytics-workshop

AWS Realtime Web Analytics Workshop with Kinesis Data Analytics

redshift-application-api

redshift-data-api-with-step-functions-sample

redshift-etl-automation-with-dbt

redshift-etl-framework

redshift-immersionday-labs

This GitHub project provides a series of lab exercises which help users get started using the Redshift platform.

redshift-jdbc-plugin-for-siteminder

redshift-query-html-ses

This project is to show how you can query a Redshift table, change fields from the query results to a clickable link, change the query results to HTML styles, and finally send an email to specified recipients using Amazon SES.

refactorspaces-operator

regulated-mlops-using-amazon-sagemaker

This project shows steps to build an end to end MLOps architecture that covers data prep, model training, realtime and batch inference, build model registry, track lineage of artifacts and model drift detection. It utilizes SageMaker Pipelines that offers machine learning (ML) to orchestrate SageMaker jobs and author reproducible ML pipelines.

reinvent-2017-deeplens-workshop

A reference Lambda function that predicts image labels for a image using a MXNet built deep learning model

reinvent-2018-social-news-app

Build a social news app.

reinvent-fine-tune-mxnet-model-for-ios-coreml

Python code, deep learning models and associated jupyter notebooks to be used by the participants of the deep learning workshop at re:Invent 2017 (MCL311).

reinvent2013-js-blog-demo

Demo blogging application using the AWS SDK for JavaScript in the browser

reinvent2013-mobile-photo-share

reinvent2014-scalable-site-management

reinvent2015-dev309

Code examples for the AWS re:Invent 2015 presentation "Large Scale Metrics Analysis in Ruby"

reinvent2018-arc329-builders-workshop

Re:Invent 2018 ARC329 Builder Workshop

reinvent2018-dev303-code

Code accompanying AWS re:Invent workshop DEV 303 showcasing how to get deep application insights using Amazon EKS with AWS X-Ray and Amazon CloudWatch.

reinvent2018-srv404-lambda-sagemaker

SRV404 Building Your Own ML Application with AWS Lambda and Amazon SageMaker

reinvent2019-aim362-sagemaker-debugger-model-monitor

Build, train & debug, and deploy & monitor with Amazon SageMaker

reinvent2019-iot335-code

Code snippets for re:Invent 2019 chalk talk "Implementing multi-region AWS IoT - IOT335"

reinvent2019-svs217

Walkthrough for re:Invent 2019 SVS217 builder session: Package your app for the AWS Serverless Application Repository

reinvent2020-aim404-productionize-r-using-amazon-sagemaker

Customers using R can run simulation and machine learning securely and at scale with Amazon SageMaker while also reducing the cost of development by using the fully elastic resources in the cloud. In this demo, learn how to build, train, and deploy statistical and ML models in R at scale using Amazon SageMaker from your IDE.

reinvent2020-predict-anomaly-in-iot-systems

reinvent2021-aim408-high-performance-cost-effective-model-deployment-amazon-sagemaker

This repo contains demo code for reInvent2021 session AIM408 Achieve high performance and cost-effective model deployment

reinvent2021-smarter-pharmacovogilance-using-aws-machine-learning

reinvent2021-tsa-bot

T. S. A. Bot is a humanoid robot, powered by AWS, that can assist with the security screening process at the airport. You can customize the bot to fit your use-case using AWS services, for example, Amazon Lex for chatbot with conversational AI, Amazon Rekognition for computer vision (CV) capabilities, Amazon Polly to convert from text to speech.

rekognition-congestion-monitoring

This is a sample web application for monitoring facility congestion using Amazon Rekognition. Images taken with a webcam are sent to the cloud, and the number of people in the images is calculated based on the response of Amazon Rekognition. Using AWS AppSync to notify end users of the number of facilities in real time. The backend of this application is developed by Amplify CLI.

rekognition-crowded-demo