Deployment of ML models with FastAPI and Uvicorn

I’m excited to share a new project on my GitHub repository that demonstrates how to deploy a machine learning model as a web service using FastAPI and Uvicorn. This project focuses on a Breast Cancer classification model trained with a Random Forest Classifier.

What you’ll find in the repository#

• Pre-trained model: The repository includes a pre-trained model ready for deployment.
• FastAPI implementation: Learn how to set up a FastAPI server to create an endpoint for your machine learning model.
• Easy deployment with Uvicorn: Step-by-step instructions on how to run your FastAPI application using Uvicorn.

Get started#

Visit the GitHub repository to clone the project, follow the setup instructions, and start deploying your own machine learning model endpoints.

This project is a great starting point for anyone looking to integrate machine learning models into their applications quickly and efficiently. Contributions and feedback are welcome!

Happy coding!