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Python SDK and Proxy Server for calling 100+ LLM APIs with cost tracking and guardrails
A collection of Jupyter notebooks showcasing how to build and deploy machine learning models with Amazon SageMaker.
A Python library for probabilistic time series modeling and forecasting, useful for data scientists and ML engineers.
This GitHub repository provides AI and Machine Learning tutorials and examples using Kubeflow, Amazon EKS, and SageMaker.
A PyTorch-based framework for reproducible deep learning studies with 26 knowledge distillation methods.
A comprehensive solution to deploy a multi-LLM and multi-RAG powered chatbot using AWS CDK on AWS.
Implementation of business use cases for safely utilizing generative AI in AWS services and applications.
Guidance for training an AWS DeepRacer model using Amazon SageMaker, providing developers full control over the process.
One-stop shop for running AI/ML on AWS with Docker, EC2, ECS, EKS, and SageMaker
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