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WebSite-Classifier is a machine learning project that classifies websites based on their content. The repository includes code for web scraping, data cleaning, feature extraction, and model building using scikit-learn and pandas. In addition, the project includes a Flask module for deploying the model.

License: MIT License

Python 24.80% CSS 60.60% HTML 13.94% Procfile 0.03% Dockerfile 0.63%

website-classifier's Introduction

📚 WebSite-Classifier 🌐

Welcome to the WebSite-Classifier repository! This is a machine learning project that can classify websites into different categories based on their content. This repository contains the code and necessary files to build and train a website classifier model.

📋 Table of Contents

Installation
Usage
Dataset
Model Training
Contributing
License

💻 Installation

To use this project, you will need to install the necessary dependencies. You can do this using pip:

pip install -r requirements.txt

🚀 Usage

The main script for this project is classify.py. To use it, simply run the following command:

python classify.py <url>

📊 Dataset

The dataset used for training this model is not included in this repository. However, you can find the dataset here

🤖 Model Training

To train the website classifier model, you can run the train.py script. This will use the dataset to train a machine learning model and save it to disk.

🚀 Flask Deployment

This project also includes a Flask web application for deploying the website classifier model. To run the Flask app, execute the following commands:

export FLASK_APP=app.py
flask run

The app will be available at http://127.0.0.1:5000/. You can enter a website URL and click the "Classify" button to classify the website into one of several categories.