Date: Nov 2022
Designed supervised and unsupervised models such as SVM, Random Forest, XGBoost, Logistic Regression etc... and trained on parkinson’s disease dataset publicly available in kaggle platform. Achieved a highest accuracy score about 80% and the lowest about 65%, tested on ten supervised and unsupervised ML models, with supervised models generally having a higher accuracy score. Utilized the Python tools such as Pandas, Numpy, Matplot, Scikit in preparing and visualizing the dataset.