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Machine learning vs deep learning: Which one is better?

Read more about how machine learning and deep learning differ, where each is used, and how businesses choose between them in ...
IEEE

Enhancing Machine Learning Algorithms for Imbalanced Data. A Case Study: Spam Detection

Abstract: Nowadays, emails are among the most common and cost-effective ways to share and exchange information. However, because of their simplicity, they are highly vulnerable to various threats. In ...
IEEE

Analysis of spam detection techniques using machine learning

Abstract: In recent years, the receipt of spam by billions of users around the world has increased. In general, for spam emails are admitted all emails that is sent without the express consent of the ...
GitHub

Machine Learning spam classifier achieving 98% accuracy using SVM, NLP, and TF-IDF vectorization

An intelligent spam detection system that classifies SMS/email messages with 98.48% accuracy using machine learning. This project compares multiple algorithms and provides comprehensive performance ...
GitHub

MusXIII/SMS_SPAM_DETECTION

This project implements a machine learning model to classify SMS messages as "spam" or "ham" (not spam) using Decision Trees and TF-IDF vectorization. CS_Project_II/ ├── dataset/ │ └── spam.csv # SMS ...
EurekAlert!

Attention detection using EEG signals and machine learning: A review

An overview of attention detection using EEG signals, which includes six steps: an experimental paradigm design, in which the task and the stimuli are defined and presented to the subjects; EEG data ...
Scientific Research Publishing

Machine Learning-Based Outlier Detection in Long-Term Climate Data: Evidence from Burkina Faso’s Synoptic Network ()

Laboratoire de Matériaux et Environnement (LAME), Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso. In recent decades, the impact of climate change on natural resources has increased. However, ...