Phishing is typically the initial step in an attempt to breach data. Machine learning enhances the detection rates for phishing by analyzing email patterns, URLs and sender behavior to identify ...

The study begins by identifying key deficiencies in traditional spam filtering systems. Classic rule-based methods and machine learning classifiers such as Naïve Bayes, Support Vector Machines (SVM), ...

Microsoft says it mitigated a known issue in one of its machine learning (ML) models that mistakenly flagged Adobe emails in Exchange Online as spam ... corporate data of hundreds of companies ...

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

Data science platform Kaggle is hosting a Wikipedia dataset that’s specifically optimized for machine learning applications. Data science platform Kaggle is hosting a Wikipedia dataset that ...

Insight: Dataset is imbalanced — mostly non-spam messages. Text Preprocessing: Lowercased all text. Removed punctuation, stopwords, special characters. Applied stemming to reduce words to root form.

This project develops a machine learning model to detect whether a given SMS message is spam or legitimate ("ham"). It applies natural language processing techniques to process text data and trains ...