spam-classifier

Spam Scanner is the best anti-spam, email filtering, and phishing prevention service.

a software held to act as a charm to avert spam and bring good messages

A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of emails is first used to train the classifier and then a previously unseen record is fed to predict the output.

Building a iOS Application using Apple's Core ML Framework, we will builed a Linear SVC model using sklearn library on the SMS Data, users will type a message on their iPhone and our model will then identify whether the message is a Spam or a Ham (Not spam).

Flask WebApp for Spam Detection using NLP

spam classifier with a dataset of 5000 mail

The project main goal is to classify an email as spam or not using Naive Bayes Algorithm.

Beginners' try with natural-language-processing end-to-end projects.

Spam classifier using Naive Bayes algorithm.

Spam classifier to test and train basic spam and ham emails using Naive Bayes Technique

This project classifies the email into spam and ham.

SMS Spam Detection using machine learning algorithms

Spam Classifier project for my end-of-semester project for Intro to AI class. We were a group of four people. I worked on all the Naive Bayes models.

Spamming Bot

It uses Text Extraction Feature like TF-IDF Vectorizer and simple python code, to classify the messages as spam or ham (normal).

Use the Naive Bayes algorithm to create a model that can classify dataset (https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection) SMS messages as spam or not spam

SVM model to classify SMS as spam or ham using Machine Learning

Naive Bayes Classification implementation of Spam Classifier in Python from the scratch

A simple spam classifier using Multinomial Naive Bayes

Python version of Andrew Ng's Machine Learning Course.

Image Spam Buster - Hackathon submission for Mall91

This is a system that takes an email and classifies if it is spam or not.

The simplest way to identify mail as spam or not

Spam Classifier using Naive Bayes from scratch (with Laplace Smoothing) without use of scikit-learn.

This notebook classify emails as spam and ham.

Artificial Intelligence Project

Supervised machine learning using a data set of 2500 ham and 500 spam emails. Data is also split into train and test sets of various sizes to test the classifier's efficiency. (Python)

It is based on support vector machines ,first we used linear kernel for lesser featured dataset, Gaussian kernel for more complex dataset.