A First Example: Blacklist versus Learned Classifier

A worked, runnable comparison of a keyword blacklist filter against a Naive Bayes spam classifier trained with scikit-learn, including a real classification report and the real class-imbalance chart from the course's own spam corpus.

~5 min total·4 quadrants of structured content

By the end of this topic, you will

Explain why a keyword blacklist fails the moment an attacker changes one word
Train and evaluate a Naive Bayes spam classifier with scikit-learn, from CountVectorizer to classification_report
Read a precision/recall/F1 classification report and connect it to real class imbalance in the training data

Quadrant 1 · e-Tutorial

Video lectures and walkthroughs

Video content coming soon.

Quadrant 2 · e-Content

Articles and case studies

A First Example: Blacklist versus Learned Classifier

A blacklist filter has no memory of anything it was not explicitly told. A learned classifier generalises to vocabulary it has never seen labelled before. Here is the code for both, side by side.

Quadrant 3 · Web Resources