Data Product

Our data product was produced using Streamlit.

We have used Pickle to save two machine learning models, each used to predict MMSE and GDS15, respectively.

Users need to answer the form that consists only of the top best features in demographic, domains. The prediction of MMSE and GDS15 will then be made using our data product.

Steps to create a Streamlit Application

1. Save machine learning models into Pickle so they can be loaded for prediction.

2. Create a Phyton file named api.py and code it with a text editor. We used Visual Code Studio to do our coding.

3. Import Streamlit and other necessary libraries.

4. Deploy Streamlit app using services provided in Streamlit.