Reduced dopamine exudation is the cause of the neurodegenerative condition Parkinson's disease (PD), which progresses over time. It has evolved into a global health issue in recent years. It will be possible to lessen the severity of the illness by identifying the source of the issue early on. A number of deep learning and algorithms for machine learning were evaluated to raise the predictability of Parkinson's disease in people who may be at risk. This study provides an in-depth analysis of various Deep learning and machine learning algorithms that are used in Parkinson's disease classification and prediction. This review also includes specifics of findings from numerous researchers that are published in the literature and pertain to the prediction process.