Giter VIP home page Giter VIP logo

nourish-net's Introduction

NourishNet (Group 2)

Welcome to the NourishNet Project! This initiative, part of the Advanced Database Topics course, addresses childhood malnutrition, a critical global issue, using advanced data analysis methods.

Project Overview

Childhood malnutrition poses significant health risks worldwide. The NourishNet Project aims to combat this challenge by employing advanced data analysis techniques and Gemini AI to understand the intricate relationship between diet and malnutrition.

Live Demo

NourishNet

Features

  • Integration of advanced data analysis techniques such as ARIMA, K-Means clustering, PCA.
  • Utilization of Gemini AI for textual insights and recommendations.
  • Examination of 51 dietary factors to uncover hidden patterns and identify malnutrition hotspots.
  • User-friendly interface empowering stakeholders to devise targeted interventions.
  • Visualization of results to highlight global malnutrition trends and dietary patterns.
  • Access to various datasets for analysis.

How to Use

  1. Clone the repository to your local machine.
  2. Install the necessary dependencies specified in the requirements.txt file.
  3. Run the NourishNet.py file to start the application.
  4. Explore the user-friendly interface to access analysis results and insights.
  5. Customize analysis by selecting different filters and parameters.

Run Locally

Clone the project

  git clone https://github.com/kishanmodi/Nourish-Ne.git

Go to the project directory

  cd Nourish-Net

Install dependencies

  pip3 install -r requirements.txt

Start the server

  python3 NourishNet.py
  streamlit run NourishNet.py

Datasets

  1. Global Dietary Database
  2. UNICEF JME Data Warehouse

Folder Structure

  • data/: Contains datasets used for analysis.
  • pages/: Include Pages of each Section.
  • NourishNet.py: Main Python script to run the application.

Contributors

  • Kishan Modi
  • Meet Patel
  • Malhar Raval
  • Aditya Tohan

License

This project is licensed for the Advanced Database Topics course at the University of Windsor during the Winter term of 2024.

Acknowledgments

We express gratitude to Dr. Shafaq Khan, our instructor, GAs and our peers for their invaluable guidance and support throughout the development of this project.

nourish-net's People

Contributors

kishanmodi avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.