The project leverages Naive Bayes Classifiers, a family of algorithms based on Bayes’ Theorem, which presumes independence between predictive features. This theorem is crucial for calculating the likelihood of a message being spam based on various characteristics of the data.

• Updated May 9, 2025
• Jupyter Notebook

Android application which uses openlysis back end.

• Updated Oct 10, 2025
• Kotlin

• Updated Oct 13, 2023
• Jupyter Notebook

Spam SMS Detection using Machine Learning is a text classification project that identifies whether an SMS is spam or not. It uses NLP techniques for text preprocessing and a machine learning model to accurately detect unwanted messages.

• Updated Jan 17, 2026
• Jupyter Notebook