Nir Shney-dor's repositories
amazon-ecs-catsndogs-workshop
This is a self-paced workshop designed to allow developers and system administrators to get hands on with Amazon Elastic Container Service concepts such as service and container-instance auto-scaling, spot-fleet integration, container placement strategies, service discovery, secrets management with AWS Systems Manager Parameter Store, time-based and event-based scheduling, and automated deployment pipelines.
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
amazon-sagemaker-mlops-workshop
MLOps workshop with Amazon SageMaker
amazon-sagemaker-notebook-instance-lifecycle-config-samples
A collection of sample scripts to customize Amazon SageMaker Notebook Instances using Lifecycle Configurations
aws-alexa-lambda-workshop
A basic Amazon Alexa Skill building workshop running with an AWS Serverless Backend
aws-dbs-refarch-datalake
Reference Architectures for Datalakes on AWS
aws-doc-sdk-examples
Welcome to the AWS Code Examples Repository. This repo contains code examples used in the AWS documentation, AWS SDK Developer Guides, and more. For more information, see the Readme.rst file below.
aws-lambda-docker-serverless-inference
Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.
ChurnWorkshop
Amazon SageMaker Churn Workshop
codepipeline-helloworld
Sample code to create a full AWS CodePipeline and deploy automatically into ElasticBeanstalk
eb-node-express-sample
Sample Express application for AWS Elastic Beanstalk
ElasticBeasnstalk-cicd-demo
This repository is used to deploy code on elasticbeanstalk. It contains php application
end-to-end-ml-sm
End to end Machine Learning with Amazon SageMaker
examples
Serverless Examples – A collection of boilerplates and examples of serverless architectures built with the Serverless Framework on AWS Lambda, Microsoft Azure, Google Cloud Functions, and more.
lambda-refarch-imagerecognition
The Image Recognition and Processing Backend reference architecture demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition.