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email-spam-classifier

Problem Statement

Email spam, unsolicited and often deceptive messages, continues to be a significant problem for individuals and organizations alike. Traditional filtering methods often struggle to keep up with evolving spam techniques. Machine learning come to the rescue and serves as an antidote to help counter this.

Objective

Train two machine learning models (Logistic regression and Naive Bayes which is based on Bayes Therorem which takes a test result and relates it to the conditional probability of that test result given other related events.

About the data

The data is gotten from www.kaggle.com and consisto Category and message. The Category being the target variable and the message being the independet Variable.

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