Top 26 sagemaker open source projects

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

SyntheticSun is a defense-in-depth security automation and monitoring framework which utilizes threat intelligence, machine learning, managed AWS security services and, serverless technologies to continuously prevent, detect and respond to threats.

Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.

CLI for building Docker images in SageMaker Studio using AWS CodeBuild.

Get notified for Instances mistakenly left running across all AWS regions for specific AWS Account

Toolkit for running PyTorch training scripts on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.

This repository provides AI/ML service(MachineLearning model serving) modernization solution using Amazon SageMaker, AWS CDK, and AWS Serverless services.

Hands-on demonstrations for data scientists exploring SageMaker

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

MLOps workshop with Amazon SageMaker

This code is used to build & run a Docker container for performing predictions against a Spark ML Pipeline.

A collection of localized (Korean) AWS AI/ML workshop materials for hands-on labs.

A containerized REST API around OpenAI's CLIP model.

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Sample code for AWS data service and ML courses on LinkedIn Learning

Know How Guide and Hands on Guide for AWS

This repository focuses on training semantic segmentation models to predict the presence of floodwater for disaster prevention. Models were trained using SageMaker and Colab.

A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources for Academic Researchers new to AWS

This is the Docker container based on open source framework XGBoost (https://xgboost.readthedocs.io/en/latest/) to allow customers use their own XGBoost scripts in SageMaker.

Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!

Public reusable components for Polyaxon

An End to End Customer Churn Prediction solution using AWS services.

This Repo Contains Deployment of Machine Learning Models on various cloud services like Azure, Heroku, AWS,GCP etc

Build and deploy a serverless data pipeline on AWS with no effort.

Projects developed by Domino's R&D team

Managed Machine Learning Systems and Internet of Things Live Lesson