Using Python and Machine Learning Algorithms to Create a Spam Classifier

Many email systems now feature spam filters that can distinguish between spam and non-spam communications. As a result of the high demand and vast user base, there is a surge in unwanted emails, sometimes known as spam emails. On several occasions, more than half of the emails received were spam. People continue to lose millions of dollars as a result of phishing emails. The goal of this study is to create a spam filter. SVM is a prominent classifier, thus it was utilised alongside two other machine learning algorithms, random forest and radial basis function, and when compared, random forest outperformed the other classifiers by 94 percent.