![]() ![]() ![]() To explain the binary classification problem, performance measures for classification, methods based on probabilities and distance measures and more advanced and state-of-the-art methods of prediction of data. To explain cheat sheet and project on descriptive analytics and generalization, performance measures for regression and the bias–variance trade-off. To explain methods involving clustering, frequent pattern mining, which aims to capture the most frequent patterns. phase of the CRISP-DM methodology, concerning data quality issues, converting data to different scales or scale types and reducing data dimensionality. To explain multivariate descriptive statistics methods of data analytics, methods used in the data preparation. To explain introductory concepts, a brief methodological description and some descriptive statistics of data. ![]()
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