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This project is an application for classifying the quality of coconuts using the K Nearest Neighbors algorithm. It is built with Streamlit for easy deployment.

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ammarsufyan/Coconut-Quality-Classification-Streamlit

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Coconut Quality Classification Streamlit

This project is an application for classifying the quality of coconuts using the K Nearest Neighbors algorithm. It is built with Streamlit for easy deployment.

Installation

  1. Clone the repository:

    git clone https://github.com/your-username/tesiscoconut.git
  2. Install the required dependencies:

    pip install -r requirements.txt

Usage

  1. Run the Streamlit app:

    streamlit run app.py
  2. Access the app in your web browser at http://localhost:8501.

Deployment

The app is deployed using Streamlit, which provides a simple and interactive user interface for the classification task. The code for the app can be found in the streamlit_app.py file.

About

This project is an application for classifying the quality of coconuts using the K Nearest Neighbors algorithm. It is built with Streamlit for easy deployment.

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