• M.Sravya
• Mrs.P. Madhavi

Spam emails, which include unsolicited, fraudulent, and malicious content, pose significant threats such as phishing attacks, dissemination of malware, and resource wastage. This project aims to propose a machine learning based approach by implementing the machine learning algorithm for the spam email detection. Email system is one of the most effective and commonly used sources of communication. The reason of the popularity of email system lies in its cost effective and faster communication nature The spam mail detection system classifies the email into spam and ham emails. The text-based email dataset considered is initially pre-processed for efficient feature extraction. Existing System All mails have a common structure i.e. subject of the email and the body of the email. A typical spam mail can be classier by altering its content

dataset, spam mail detection, accuracy, database, Natural language processing, spam/harm emails

"AN EFFECTIVE SPAM MAIL DETECTION USING NATURAL LANGUAGE PROCESSING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.483-486, June-2024, Available :http://www.jetir.org/papers/JETIRGL06080.pdf

"AN EFFECTIVE SPAM MAIL DETECTION USING NATURAL LANGUAGE PROCESSING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp483-486, June-2024, Available at : http://www.jetir.org/papers/JETIRGL06080.pdf