Stars
A Datacenter Scale Distributed Inference Serving Framework
An NVIDIA AI Workbench example project for Retrieval Augmented Generation (RAG)
Foundation model benchmarking tool. Run any model on any AWS platform and benchmark for performance across instance type and serving stack options.
Hands-on workshop for distributed training and hosting on SageMaker
Compilation of examples of SageMaker inference options and other features.
Deploy a pre-trained Sklearn Model on Amazon SageMaker
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
brightsparc / amazon-sagemaker-drift-detection
Forked from aws-samples/amazon-sagemaker-drift-detectionThis sample demonstrates how to setup an Amazon SageMaker MLOps end-to-end pipeline for Drift detection
In this repository, we will present techniques to detect covariate drift, and demonstrate how to incorporate your own custom drift detection algorithms and visualizations with SageMaker model monit…
Scale-Out Computing on AWS is a solution that helps customers deploy and operate a multiuser environment for computationally intensive workflows.