You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
These are some of the projects that I have worked on while taking the Machine Learning course at UT Dallas under Prof Anjum Chida in Spring 16. Assignment 2 consists of Naive Bayes and Logistic Regression codes for classifying emails as either spam or ham. Assignment 3 consists of Image segmentation using K-Means and Perceptron algorithm for ema…
The app takes email input in text format from the user and accurately classifies it either as spam or ham (not spam) with an overall accuracy of 95%. You can access the app using the link below.
This repository contains a Python script that uses various machine learning models to classify spam messages from ham messages. The model is trained on a Popular dataset of Spam emails and we use multiple machine learning models for classification.