ABSTRACT
Parkinson's disease (PD), is neurological disorder that progresses slowly and causes major damage. The impact of nerve cells in a small part of the mind are known as substantia nigra are liable for generating a chemical known as dopamine. Body movements will be affected due to the loss of dopamine. Reduction in dopamine levels causes abnormality in brain activities which leads to difficulties in speaking, writing, and walking. Ninety percent of people are affected by PD. The PD is affects those over the age of 50, and frequency increases substantially with age. There are about 60,000 cases discovered per year. There is no exact cure for Parkinson's disease as of now, but studies and research are going on, and regular medication or surgery can help to abate the symptoms of Parkinson's disease.
Parkinson's disease (PD) is one of the serious diseases; hence estimating it at an earlier stage helps in treating PD patients and lessens the effects. For diagnosing the disease in earlier stages, it's discovered that the machine learning classification algorithm is one of the pleasant methods. In this work, we illustrate how Amazon Sage Maker's algorithm solving applications require machine learning models for prediction. For this instance, we've taken an example for Parkinson's disease prediction and the use of Parkinson's disease data from the UCI machine learning repository.
