https://github.com/nameisparker/diabetes_predictor

https://github.com/nameisparker/diabetes_predictor

Last synced: 3 months ago
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• Host: GitHub
• URL: https://github.com/nameisparker/diabetes_predictor
• Owner: Nameisparker
• Created: 2024-08-25T17:15:20.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-08-25T17:25:27.000Z (10 months ago)
• Last Synced: 2025-01-14T11:58:18.630Z (5 months ago)
• Language: Jupyter Notebook
• Size: 39.1 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
End-to-End Diabetes Prediction Application using Machine Learning 

In this project, the objective is to predict whether the person has Diabetes or not based on various features such as

Pregnancies

Insulin Level

Age

BMI.

The data set that has used in this project has taken from the kaggle . "This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage." and used a simple random forest classifier.

Motivation

The motivation was to experiment with end to end machine learning project and get some idea about deployment platform like Heroku and offcourse this " Diabetes is an increasingly growing health issue due to our inactive lifestyle. If it is detected in time then through proper medical treatment, adverse effects can be prevented. To help in early detection, technology can be used very reliably and efficiently. Using machine learning we have built a predictive model that can predict whether the patient is diabetes positive or not.". This is also sort of fun to work on a project like this which could be beneficial for the society.

Learning Objective

The following points were the objective of the project . If you are looking for all the following points in this repo then i have not covered all in this repo. I'm working on blog about this mini project and I'll update the link of blog about all the points in details later . (The main intention was to create an end-to-end ML project.)

Data gathering

Descriptive Analysis

Data Visualizations

Data Preprocessing

Data Modelling

Model Evaluation

Model Deployment

Technical Aspect

Training a machine learning model using scikit-learn.

Building and hosting a Flask web app on Heroku.

A user has to put details like Number of Pregnancies, Insulin Level, Age, BMI etc .

Once it get all the fields information , the prediction is displayed on a new page .

Technologies Used

    

Bug / Feature Request

If you find a bug (the website couldn't handle the query and / or gave undesired results), kindly open an issue here by including your search query and the expected result.

If you'd like to request a new function, feel free to do so by opening an issue here. Please include sample queries and their corresponding results.

Installation

Clone this repository and unzip it.

After downloading, cd into the flask directory.

Begin a new virtual environment with Python 3 and activate it.

Install the required packages using pip install -r requirements.txt

Execute the command: python app.py