SageMaker custom deployments made easy

This is a terraform and github actions wrapper on "Amazon SageMaker AI MLOps: from idea to production in six steps" to make it easier to deploy and tear down.

This project demonstrates the fine-tuning of a Large Language Model (LLM) using multiple datasets to enhance its performance. The model is deployed using an Amazon SageMaker endpoint, enabling easy integration with other AWS services.

Guide for easy custom PyTorch model deployment on Amazon SageMaker, with practical code examples.

make it easier to deploy and manage your own ML model(TensorFlow Framework) with Amazon SageMaker.

This repository contains a comprehensive solution for predicting phone prices using a machine learning pipeline built with Amazon SageMaker, Scikit-learn, and a Random Forest Classifier. The project covers data preprocessing, training, evaluation, and deployment, making it easy to integrate and expand for further use cases.