In this chapter, we kick off our machine learning classification journey with spam email detection. It is a great starting point of learning classification with a real-life example-our email service providers are already doing this for us, and so can we. We will be learning the fundamental and important concepts of classification, and focusing on solving spam detection using a simple yet powerful algorithm, naive Bayes.

The outline for this chapter is as follows:

• What is classification?
• Types of classification
• Text classification examples
• Naive Bayes classifier
• The mechanics of naive Bayes
• The naive Bayes implementations
• Spam email detection with naive Bayes
• Classification performance evaluation
• Cross-validation
• Tuning a classifier