Kidney Disease Prediction Project - ADVANCED classification TECHNIQUES

🔍 ABOUT THIS PROJECT

The aim of this project is to analyze a dataset in order to develop a machine learning model and predict Kidney Disease Prediction to Marathon data science https://cientistadedadosnapratica.com.br/jornada_fev22?blog=z8te2pr0&video=29djsmyi3 in https://cienciadosdados.com

Using algorithm

###GradientBoost https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html

###RandomForest https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html

Notebook

https://github.com/robertoricci/Kidney-Disease/blob/main/Images/Kidney.ipynb

Demo

If you want to view the deployed model, click on the following link:

• https://app-kidney-disease.herokuapp.com/

Dataset

Chronic Kidney Disease Dataset

Dataset Description

Download Description

Tech Stack

• Python
• Machine Learning
• Pandas
• Numpy
• Scikit-learn
• Flask
• HTML
• CSS
• Heroku
• Flask

Deployment

To deploy this project run following command in the project folder

Clone the code repository

  https://github.com/robertoricci/Kidney-Disease.git

virtualenv venv

  python -m venv .venv

virtualenv activate

  source env\Scripts\activate

Install

  pip install -r requirements.txt

Runn

  flask run

Screenshots

Deployment on Heroku

Heroku login on git bash

  heroku login

Create new app

  heroku create

Push Code

  git remote -v

Push code to Master Branch

  git push heroku main

Feedback

If you have any feedback, please reach out to me at https://www.linkedin.com/in/roberto-carlos-ricci/

Please do ⭐ the repository, if you like this 😊

Thank you ❤