Project of a Web App that performs predictions based on a machine learning model

Description

This project consists of a web app that receives data from a user and returns a message with the diagnosis according to the prediction of a machine learning model of the Random Forest Classifier type. The trained model was serialized and uploaded to the site. Whenever the input values are changed, the forecast is made.

A Random Foresc Classifier model was created and tuned. The overall accuracy achieved was 84.42%

Access

Link to web app: http://ferris77.pythonanywhere.com/

Acknowledgements

1. Smith, J.W., Everhart, J.E., Dickson, W.C., Knowler, W.C., & Johannes, R.S. (1988). Using the ADAP learning algorithm to forecast the onset of diabetes mellitus. In Proceedings of the Symposium on Computer Applications and Medical Care (pp. 261--265). IEEE Computer Society Press. 2. https://www.kaggle.com/uciml/pima-indians-diabetes-database

About

This is one of my first projects in my Machine Learning studies. Feedbacks and impressions are most welcome :)