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Simple Classification Problem-labelling emails as spam or non spam based on content. dataset from UCI machine learning repository.

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Guiding our analysis is the Disc Consulting (DCE) data on IP Packet event records, that has identified malicious and non-malicious event record within their networks and computer systems, for which the attacks are more sophisticated than previously experienced attacks, with no clue on the methods used for intrusion.

A suggested approach is incorporate a real-time threat detection system based on machine learning classification models to categorize an record event as either malicious or not based on IP packets attributes. Performance measures and model selection, will be assessed inline with the scope of the DCE objectives.

The Titanic data set provides a sample of passengers, with some basic details: their names, ages, gender, class, and several others. We are predicting a binary response: whether the passenger survived or died.

Data

The Spambase Data Set was obtained from the UCI Machine Learning Repository.

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Simple Classification Problem-labelling emails as spam or non spam based on content. dataset from UCI machine learning repository.

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