Ending spam : Bayesian content filtering and the art of statistical language classification An introduction to spam filtering concepts The history of spam Historical approaches to fighting spam Next generation filtering Shining examples of filtering Machine learning concepts Fundamentals of statistical filtering Statistical filtering fundamentals Decoding: uncombobulating messages Tokenization: the building blocks of spam Open source OSX and Milk Duds The low down dirty details of spam Data storage for a zillion records Scaling for large scale environments Advanced concepts of statistical filtering Concept identification: advanced tokenization Testing theory Fifth order Markovian discrimination Concept identification: advanced tokenization Intelligent feature set reduction Collaborative algorithms Installing and using open source filters.