Scalable Machine Learning Model for Accurate Predictions on AWS

In this project, we’ll use PyCaret, a Python library for machine learning, to create a predictive model for diabetes.

Once the model is built and finalized, we’ll store it on AWS S3, a scalable storage service. This will allow us to store the model and make it available for other applications.

After deploying the model, we’ll create a Python script to load it and use it to make predictions on new data. This will allow us to test the model and ensure it works as expected.

Finally, we’ll use FastAPI, a modern, high-performance web framework for building APIs, to create a web application allowing users to interact with the model. This application will take input from the user and use the deployed model to predict whether an individual has diabetes.