This project focuses on detecting Parkinson’s disease using machine learning techniques. By applying Support Vector Machines (SVM) for classification, I developed a model that effectively diagnoses Parkinson’s disease. The model underwent various data handling and pre-processing steps to ensure high accuracy and reliability, ultimately achieving an 89% accuracy in predictions.