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https://github.com/adadalshabab/diabetes_prediction_ml_app
https://github.com/adadalshabab/diabetes_prediction_ml_app
Last synced: about 1 month ago
JSON representation
- Host: GitHub
- URL: https://github.com/adadalshabab/diabetes_prediction_ml_app
- Owner: AdadAlShabab
- Created: 2023-05-28T06:10:25.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-03-16T17:23:38.000Z (10 months ago)
- Last Synced: 2024-03-16T23:35:48.071Z (10 months ago)
- Language: Python
- Size: 36.1 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
### Overview
In this project, the objective is to predict whether the person has Diabetes or not based on various features suach as
- Pregnancies
- Insulin Level
- Age
- BMI
- Blood Pressure
- Sugar Level.
The data set that has used in this project has taken from the [kaggle](https://www.kaggle.com/) . "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.I've used a simple [random forest classifier](https://en.wikipedia.org/wiki/Random_forest) to predict the outcome.
### Motivation
The motivation was to experiment with end to end machine learning project and get some idea about deployment platform like [Streamlit](https://streamlit.io/) 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.
### Demo
[Visit this link for live demo](https://diabetes-detection-ml.streamlit.app/)
### 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
### Installation
- Clone this repository and unzip it.
- 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