sagemaker

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

Probabilistic time series modeling in Python

A library for training and deploying machine learning models on Amazon SageMaker

A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS

Application implementation with business use cases for safely utilizing generative AI in business operations

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

AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.

LLMs and Machine Learning done easily

Amazon SageMaker Local Mode Examples

Foundation model benchmarking tool. Run any model on any AWS platform and benchmark for performance across instance type and serving stack options.

This repo provides sample generative AI stacks built atop the AWS Generative AI CDK Constructs.

This repository includes code and demos for session "Unlock insights with AWS GenAI services" (re:Invent BOA303)

A collection of personally developed projects contributing towards the advancement of Artificial General Intelligence(AGI)

Seamlessly invoke Amazon Bedrock or your custom models, enabling a smooth experience with AWS GenAI services.

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

Deploy open-source LLMs on AWS in minutes — with OpenAI-compatible APIs and a powerful CLI/SDK toolkit.

AI Makerspace: Blueprints for developing AI applications with cutting-edge technologies.

Demonstration application showing how Neo4j works with Amazon Bedrock

This project demonstrates how to generate images using Stable Diffusion or FLUX.1 models by hosting ComfyUI on Amazon SageMaker inference endpoint.

Generative AI on AWS Immersion Day