Email Spam Detection using Machine Learning
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Updated
Jul 20, 2023 - Jupyter Notebook
Email Spam Detection using Machine Learning
An Email Spam Classifier project, helps you detect your spam email from correct email. Try it out here!
Identifying and distinguishing spam SMS and Email using the multinomial Naïve Bayes model.
Implemented Preprocessing steps, Feature Extraction techniques and Naive Bayes Classifier in C++. Moreover, we have also implemented all the steps using python for comparative analysis.
One of the primary methods for spam mail detection is email filtering. It involves categorize incoming emails into spam and non-spam. Machine learning algorithms can be trained to filter out spam mails based on their content and metadata.
Would you like to know which e-mail is spam and which is ham?
This is an Email/SMS spam detection system, built as a project for AutumnnHacks Hackathon. It classifies messages you recieve on emails and sms as spam or not spam.
An end-2-end project
This Python code compares the performance of k-Nearest Neighbors (k-NN) and Multi-Layer Perceptron (MLP) classifiers using a dataset from 'spambase.csv,' evaluating accuracy, precision, recall, and F1 score for each model.
This machine learning project implements an advanced email spam detection system using Python and scikit-learn. By leveraging Multinomial Naive Bayes classification, the system accurately distinguishes between spam and legitimate (ham) emails.
Email Spam Detection Using Logistic Regression
This project is to classify emails as spam or not spam using various machine learning models. Hyperparameter tuning is performed to optimize model performance.
A email spam classifier based on Multinomial Naive Bayes model and running on Streamlit.
An email spam detection system with ML and Python
Classify the message is spam or not using Multinomial Naive Bayes.
Email-Spam-Classifier using Naive Bayes Algorithm
To check email is spam or not spam
Email Spam detection using Machine Learning
Email spam classification for Naive Bayes, Gradient Boosting Machine, Support Vector Machine and Random Forest
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