During a pulse oximetry reading, a small clamp-like device is placed on a finger, earlobe, or toe. Small beams of light pass through the blood in the finger, measuring the amount of oxygen. It does this by measuring changes of light absorption in oxygenated or deoxygenated blood
It measure your SpO2 (oxygen saturation level) with the help of body measurements.
The dataset used for modeling is taken from Kaggle.
Since the dataset is not real but synthetic, predictions need not to be taken seriously.
The Navigation Bar on the top left corner has been added to access different pages.
Dashboard is created using PowerBI.
Distribution of various features are shown.
Some important ranges are mentioned which helped to categorize the dataset.
Modeling is done with the help of PyCaret.
Error analysis shows the deviation of the predicted values from the actual ones.
RMSE has been used as the main metric to optimize LGMReressor.
The framework used for this app is Streamlit and is deployed on Heroku.
