SMS Spam Detection

SMS Spam Detection Demo

Overview

The SMS Spam Detection model is a machine learning-based application that predicts whether an SMS message is spam or not spam. Built using Python and deployed on Streamlit, this tool helps users identify unwanted spam messages and improve mobile security.

How the Model Works

The model processes the SMS text by:

1. Preprocessing: Text is cleaned by converting to lowercase, removing special characters, stopwords, and punctuation.
2. Vectorization: The cleaned text is transformed into a numerical format.
3. Prediction: A trained classifier predicts whether the message is spam or not.

How It Helps People

Spam messages, often linked to phishing and unwanted ads, can be harmful. This app helps users by:

• Automatically detecting spam messages.
• Protecting users from potentially malicious content.
• Providing an easy-to-use interface to check messages for spam.

Technology Used

• Python
• NLTK (Natural Language Toolkit)
• Scikit-learn
• Streamlit
• Pickle

Demo

Try out the live SMS Spam Detection model here: SMS Spam Detection Demo