352 results for “topic:spam-classification”
Anti-spam bot for Telegram and general-purpose anti-spam library and server
🗣️ Tool to generate adversarial text examples and test machine learning models against them
Spam Scanner is a Node.js anti-spam, email filtering, and phishing prevention tool and service. Built for @ladjs, @forwardemail, @cabinjs, @breejs, and @lassjs.
ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python
Large Collection of Extensions and AspNetCore projects for ML.NET models and integration
:construction: :rocket: Spam Database and Classifiers for automated usage :construction:
Focuses on detecting spam messages in SMS text using Natural Language Processing (NLP) and Machine Learning techniques. It leverages text preprocessing, feature extraction, and classification algorithms to accurately predict whether a message is Spam or Ham (Not Spam).
Implements a machine learning-based SMS spam detection system. It classifies incoming text messages as Spam or Ham (Not Spam) using Natural Language Processing (NLP) techniques and supervised learning algorithms.
Asynchronous Python Wrapper For A.R.Q API.
A web app that classifies text as a spam or ham. I am using my own ML algorithm in the backend, Code to that can be found under machine_learning_section. For Live Demo: Checkout this link
Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification
Spam filtering module with Machine Learning using SVM (Support Vector Machines).
Detects cyber threats to the end user with machine learning. This tool can do malware analysis of given exe file, spam analysis of given url and mail.
Quick Hands-On NLTK tutorial for NLP in Python. NLTK is one of the most popular Python packages for Natural Language Processing (NLP). Easy to Start for Anyone.
Group Guardian is a Telegram bot for admins to maintain a safe community.
This is about spam classification using HMM model in python language
A simple bayesian spam classifier written in Rust.
Identifying and distinguishing spam SMS and Email using the multinomial Naïve Bayes model.
Official resource of the paper "Traditional and Context-Specific Spam Detection in Low Resource Settings", Machine Learning Journal 2022
✉️ 🐖 Spam email identification using NLP and a RNN with TensorFlow
No description provided.
An Android Project to demonstrate the use of a TensorFlow Lite model to classify spam messages.
A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of email subject is first used to train the classifier and then a previously unseen email subject is fed to predict whether it is Spam or Ham.
No description provided.
Spam Filtering Techniques for Short Message Service
使用trec06c数据集，通过jieba分词，word2vec训练词向量，搭建CNN进行垃圾邮件检测
The Spam Mail Classification project is a web-based application that uses machine learning to classify emails as spam or ham. It features a Flask backend, a frontend created with HTML, CSS, and JavaScript, and a MySQL database for storing user data and email classifications.
Flask WebApp for Spam Detection using NLP
中文垃圾评论分类
Machine Learning Exercises from Online Course (Coursera)