Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

Mistral on AWS examples for Bedrock & SageMaker

🦜🔗 Build context-aware reasoning applications

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

Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training

This repository provides a general DevOps practices such MSA, IaC, CICD and Monitoring. AWS various services are used to provide DevOps best practices.

Hands-on lab from ML model training to model compilation to edge device model deployment on the AWS Cloud. It covers the detailed method of compiling SageMaker Neo for the target device, including …

A collection of sample scripts to customize Amazon SageMaker Notebook Instances using Lifecycle Configurations

This project contains the code necessary to build an AWS AMI with monitoring capabilities of GPU usage (among other metrics) using CloudWatch.

Demos for customer about real acting features

AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker

collection of predictive maintenance solutions for NASAs turbofan (CMAPSS) dataset

Korean localization of the SageMaker Feature Store notebooks added in AWS re:Invent 2020

Deep Learning Inference hands-on labs; Learn how to host pre-trained TensorFlow/MXNet models to Amazon SageMaker Endpoint without building Docker Image

Korean localization of the SageMaker Distributed Training notebooks added in AWS re:Invent 2020

Korean localization of the SageMaker Pipelines notebooks added in AWS re:Invent 2020

A collection of loss functions for medical image segmentation