aws-samples Goto Github PK
Name: AWS Samples
Type: Organization
Blog: https://amazon.com/aws
Name: AWS Samples
Type: Organization
Blog: https://amazon.com/aws
This repository provides the resources required for the Amazon Redshift Streaming workshop
Amazon Redshift offers a common query interface against data stored in fast, local storage as well as data from high-capacity, inexpensive storage (S3). This workshop will cover the basics of this tiered storage model and outline the design patterns you can leverage to get the most from large volumes of data. You will build out your own Redshift cluster with multiple data sets to illustrate the trade-offs between the storage systems. By the time you leave, you’ll know how to distribute your data and design your DDL to deliver the best data warehouse for your business.
A collection of example UDFs for Amazon Redshift.
Automate Redshift cluster creation with best practices using AWS CloudFormation
This project deploys a fully serverless pipeline to moderate images posted to a Slack channel using the AWS CDK along with AWS Solutions Constructs. Services used are: Amazon Rekognition, Amazon AppFlow, AWS Lambda,Amazon S3 and Amazon SQS
Starter iOS Swift project code for identifying celebrities using Amazon Rekognition
Amazon Rekognition Code Samples
Amazon Rekognition Content Moderation using Amazon API Gateway and AWS Lambda
With Amazon Rekognition Custom Labels, you can easily build and deploy Machine Learning (ML) models to identify custom objects which are specific to your business domain in images without requiring advanced ML knowledge. When combined with Amazon Augmented AI (A2I), you can quickly integrate a ML workflow to capture and label images with a human workforce for model training. As ML lifecycle is an iterative and repetitive process, you need to implement an effective workflow that can provide for continuous model training with new data and automated deployment. Your workflow also needs to be flexible enough to allow for changes without requiring development rework as your business objectives change. Operationalizing an effective and flexible workflow can be resource intensive, especially for customers who have limited machine learning capabilities. In this post, we will use AWS Step Functions, AWS Lambda, and AWS System Manager Parameter Store to automate a configurable ML workflow for Rekognition Custom Labels and A2I. We will provide an overview of the solution and instructions to deploy it with AWS CloudFormation.
This project contains source code and supporting files for a serverless application which can be used for Computer Vision inferencing using Amazon Rekognition.
A demo to test Custom Labels with models trained by Amazon Rekognition
Model assisted dataset preparation for Amazon Rekognition Custom Labels.
The Engagement Meter calculates and shows engagement levels of an audience participating in a meeting
This project adds a HeatMap layer on top of a picture based on Amazon Rekognition detect labels function.
This sample, built using AWS Amplify, is meant to showcase recommended flows when using Amazon Rekognition for Identity Verification.
Sample application using Amazon Rekognition Image and S3 using Box Skills events
Detect Personal Protective Equipment using Amazon Rekognition
A Stepfunctions driven workflow to use Amazon Rekognition to scan incoming images through a set of business rules and police apply policing
Process images and videos at scale using Amazon Rekognition
A working prototype for capturing frames off of a live MJPEG video stream, identifying objects in near real-time using deep learning, and triggering actions based on an objects watch list.
A solution to assist with virtual proctoring of exams using Amazon Rekognition
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.