Deploy model with FastAPI and Heroku

1. 1Build a machine learning model using your preferred framework
2. 2Create a FastAPI application to serve the model
3. 3Configure the model to be served as an API endpoint using FastAPI
4. 4Deploy the FastAPI application to Heroku using Git and the Heroku CLI
5. 5Test the deployed model by sending requests to the API endpoint

Data scientists and machine learning engineers can benefit from this tutorial to deploy their models quickly and securely, while DevOps teams can use this as a reference for model deployment pipelines

💡 FastAPI and Heroku provide a robust and scalable way to deploy machine learning models as APIs

💡 Deploy your ML model with FastAPI and Heroku for scalable model serving