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Machine learning is the study of patterns in large, complex data sets, with the goal of making quantitative predictions and inferences about those patterns. In this talk, I will discuss Classification, perhaps the most fundamental problem in machine learning. Classification is the problem of classifying a measured pattern into one of a finite number of classes, leveraging known examples of each class. I will overview basic methodological and theoretical issues in pattern recognition.