📧 Email Spam Detection with Machine Learning

A Machine Learning project that detects whether a text message or email is Spam or Ham. This project includes a model training script and a user-friendly Graphical User Interface (GUI) built with Tkinter.

🚀 Features

• Machine Learning: Uses Logistic Regression to classify text with ~96% accuracy.
• Text Processing: Implements TF-IDF (Term Frequency-Inverse Document Frequency) to convert text into numerical features.
• GUI Application: A clean desktop interface to test custom messages instantly.
• Reproducibility: Scripts to train the model from scratch and save it for inference.

🛠️ Tech Stack

• Language: Python 3.x
• Libraries: Scikit-Learn, Pandas, NumPy, Pickle
• GUI: Tkinter (Standard Python Interface)

📂 Project Structure

SPAMCLASSIFIER/
├── .venv/                   # Virtual environment (ignored in git)
├── app.py                   # GUI Application for testing
├── main.py                  # Script to train and evaluate the model
├── spam.csv                 # Dataset file
├── README.md                # Project documentation
└── .gitignore               # Files to ignore (pkl, venv, etc.)