ML Classification: Spam Detection

This project focuses on training and evaluating ML models for spam detection using a dataset of spam emails. The workflow also includes features to release trained models automatically using GitHub Actions.

Features

• Preprocessing pipeline for data cleaning and preparation.
• Training and evaluation of machine learning models.
• Automated release workflow using GitHub Actions.
• Spam email dataset included for model training.

Getting Started

1. Clone the repository:

   git clone https://github.com/yourusername/ml-project.git
   
2. Create virtual environment:

   python3 -m venv yourvenvname   
   
3. Activate the venv (for linux):

   source yourvenv/bin/activate
   
4. Install dependencies on venv:

   pip install -r requirements.txt
   
5. Run the main.py:

   python main.py
   

Usage:

The application processes the spam dataset, trains a classification model, and provides evaluation metrics. Results are saved for further analysis or deployment.

Note:

The application may slow when startup due to the model training process on the app startup event with large dataset