Spam Email, or junk mail, refers to unsolicited messages sent in bulk to a large number of users, often containing misleading information, scams, or even phishing attempts. While spam emails can occasionally be sent manually, they are most commonly distributed by automated bots. Popular email platforms, like Gmail, use built-in filters to detect and block spam by identifying common phrases and patterns. Despite these filters being generally effective, some well-crafted spam emails may bypass detection, landing in your inbox instead of the spam folder.
Opening such emails can be risky, potentially exposing your computer and personal data to malware. This makes it crucial to adopt additional protective measures, especially if your device handles sensitive information, such as user data.
To build a robust spam detection system, we’ll use Python libraries like Pandas and Scikit-learn. Pandas is widely used for data cleaning and analysis, while Scikit-learn (also known as Sklearn) provides powerful tools for machine learning tasks, including classification, regression, clustering, and dimensionality reduction, all with a consistent interface.