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NeuralWeb

This repository contains an advanced Python script designed for web scraping, data integration, and neural network model training. It leverages BeautifulSoup for parsing HTML content, TensorFlow and Keras for building and training models, and several other libraries for data processing and automation.

Features

  • Comprehensive Web Scraping: Scrapes not only the main content from specified URLs but also navigates and extracts data from internal links.
  • Data Preprocessing: Includes text cleaning, tokenization, and sequence padding to prepare the data for model training.
  • Neural Network Model Training: Utilizes TensorFlow and Keras to build and train a neural network model on the processed data.
  • Automated Retraining: Uses schedule for automated retraining, ensuring the model stays updated with the latest web data.
  • Ethical Scraping: Includes checks against robots.txt to ensure compliance with web standards and ethical scraping practices.

Setup and Installation

Ensure you have Python 3.x installed. Clone the repository and install the required packages:

git clone https://github.com/Arkay92/NeuralWeb.git
cd NeuralWeb
pip install -r requirements.txt

Usage

Run the script to start the scraping and model training process:

python main.py

Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue for any improvements or suggestions.

License

This project is licensed under the MIT License - see the LICENSE file for details.