Text Classification for Spam Detection using Machine Learning

This project involves creating a text classification system to detect spam messages. The system uses machine learning models to classify messages as either spam or not spam based on their content.

Features

• Classifies text messages into spam or non-spam categories.
• Uses machine learning algorithms for accurate classification.
• Provides insights into the most common features of spam messages.
• User-friendly interface for inputting and analyzing messages.

Installation

To set up the spam detection system on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/spam-detection.git
   cd spam-detection

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To start the spam detection system, run the main script and input the text you want to classify:

python spam_detection.py --text "message to classify"