README.MD

Emai Spam Detection

Abstract : This project focuses on developing a spam detection system using machine learning. By training a Naive Bayes classifier on SMS data labeled as spam or non-spam, the model effectively learns to identify unwanted messages. Text processing techniques like CountVectorizer are used to convert messages into features for training. The system achieves high accuracy and demonstrates the potential of machine learning in automating spam filtering.

Deployment Steps

Please follow the below steps to run this project.

1. Clone the repository:

git clone

2. Create and activate a Python virtual environment:

On Windows:

python -m venv venv venv\Scripts\activate

On macOS/Linux:

python3 -m venv venv source venv/bin/activate

3. Install the required dependencies:

pip install -r requirements.txt

4.Run the application:

python main_updated_v2.py

5. The GUI window will open where you can enter messages to classify as spam or ham.