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dr.-claude's Introduction

Dr. Claude - Patient Care with AWS

Description

This Jupyter notebook demonstrates how to leverage AWS services and generative AI to enhance healthcare solutions. It outlines the process of creating a serverless system that provides custom medical recommendations, showcasing the practical application and benefits of integrating generative AI models in healthcare.

Installation

Before you begin, ensure you have the following pre-requisites:

  • An AWS account
  • Access to Claude 3 and Titan Embeddings models (you can request access through the AWS console)
  • A SageMaker Studio Domain

To set up the project environment, clone this repository in a terminal inside SageMaker's Jupyter Lab:

git clone https://github.com/duartemoura/Dr.-Claude.git

Usage

To run the notebook:

  • Launch your SageMaker Studio Domain
  • Create JupyterLab space if you don't have one already
  • Start JupyterLab
  • Open the llm_kb_email.ipynb file
  • Choose a kernel - Python3 (ipykernel)
  • Follow the instructions within the notebook to execute the cells

Acknowledgements

Some of the code used in this notebook was taken from the AWS Bedrock Workshop GitHub repository.

dr.-claude's People

Contributors

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