Project1-Parkinson'sdisease-Problem-Statement.md

Parkinson's disease Prediction Project

Problem Statement:

Parkinson's disease is a progressive nervous system disorder that affects movement.In this Machine learning project, we will build a model using which we can accurately detect the presence of Parkinson’s disease in one’s body.

Approach

The main goal is to detect the presence of Parkinson’s disease in one’s body with the available dataset

 
 Data Exploration     : We started exploring dataset using pandas,numpy,matplotlib and seaborn. 
 Data visualization   : Ploted graphs to get insights about dependend and independed variables. 
 Feature Engineering  :  Removed missing values and created new features as per insights.
 Model Selection I    :  1. Tested all base models to check the base accuracy.
                             2. Also ploted residual plot to check whether a model is a good fit or not.
 Model Selection II   :  Build a model with XGBoost classifier
 Pickle File          :  Selected model as per best accuracy and created pickle file using joblib .
 Webpage & deployment :  Created a webform that takes all the necessary inputs from user and shows output.
                                After that we have deployed project on heroku

Project Interface

Link : https://parkinsondiseasepredictor.herokuapp.com/

Technologies Used

 
1. Python 
2. Sklearn
3. Flask
4. Html
5. Css
6. Pandas, Numpy