In this project, I've Trained and tested three models i.e Decision Tree Classifier, XGBoost, and Random Forest to predict Parkinson’s Disease based on Speech Analysis parameters such as Frequency, Jitter, Shimmer, etc.
The DataSet for this project was taken from the UCI's Parkinson's Repository (which can be found here https://archive.ics.uci.edu/ml/datasets/parkinsons!!).