This tutorial reviews Probability starting right at ground level. It is, arguably, a useful investment to be completely happy with probability before venturing into advanced algorithms from data mining, machine learning or applied statistics. In addition to setting the stage for techniques to be used over and over again throughout the remaining tutorials, this tutorial introduces the notion of Density Estimation as an important operation, and then introduces Bayesian Classifiers such as the overfitting-prone Joint-Density Bayes Classifier, and the over-fitting-resistant Naive Bayes Classifier.

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