/Parkinsons_Diagnosis

Exploratory Data Analysis and Model Building

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PARKINSONS DIGNOSIS OF DISEASE

  • A Exploratory Data Analysis and Model building process that uses voice signals dataset identifies significant vocal features and builds a reliable predictive model. We provide a non-invasive and accurate diagnosis that enables early intervention & improves patient outcomes.

  • The dataset used in this project is from Kaggle data bank. The dataset has 24 columns, thus we need to reduce the dimension before we train the data.

  • The target or independent variable is "status" with binary values of 0 and 1. Status values for healthy person and PD person are 0 and 1 respectively. This is a classification probelm.

  • The goal is to develop the best machine learning model to predict the Parkinson's disease so that we can treat the patient in the timely manner.