Email is a widely used communication medium for formal information sharing, but spam emails pose significant challenges by wasting time, consuming bandwidth, introducing security risks such as ...

By combining machine learning-based text classification and sentiment analysis, we can create a robust AI-powered email triage system. Here’s a step-by-step guide.

Long Short-Term Memory (LSTM) network trained to classify emails as spam or non-spam. It processes email content to make accurate predictions and can be integrated into projects for efficient spam ...

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 ...

(3) For dataset classification, our hybrid deep learning model combines convolutional neural networks (CNN) and long short-term memory (LSTM), and we tuned hyperparameters to determine which settings ...

In a revolutionary move, Flow Security Unveils the First DSPM Solution to Harness Large Language Models (LLMs) in Unstructured Data Classification.

The LSTM model classified the SMS dataset effectively with the learning model. Experimental study showed that the model has achieved an accuracy of 88.33% accuracy on SMS spam classification with the ...