PinnedPublished inTDS ArchiveAn Introduction to Supervised LearningThe one with an example of the Naive Bayes classification algorithmFeb 26, 2022Feb 26, 2022
PinnedPublished inTDS ArchiveAn Introduction to Linear RegressionRegression is used primarily if you wish to predict or explain numeric dataMar 8, 2021Mar 8, 2021
PinnedPublished inTDS ArchiveBayesian StatisticsHard to believe there was once a controversy over probabilistic statisticsFeb 25, 2021Feb 25, 2021
PinnedPublished inTDS ArchiveBootstrap ResamplingNo, not Twitter Bootstrap — this bootstrapping is a way of sampling data, and it is one of the most important to consider what underlies…Feb 2, 20211Feb 2, 20211
Published inTDS ArchiveTime Series Analysis“It’s tough to make predictions, especially about the future!” — Yogi BerraJun 14, 2021Jun 14, 2021
Published inTDS ArchiveLogistic RegressionOr how I learned to love the sigmoid “squishification” function for categorical data classificationApr 13, 2021Apr 13, 2021
Published inTDS ArchiveRidge, LASSO, and ElasticNet RegressionThe continuing adventures of regularization and the eternal quest to prevent model overfitting!Apr 2, 2021Apr 2, 2021
Published inTDS ArchiveRegularization and Linear RegressionThe one where we correct overfittingMar 25, 2021Mar 25, 2021
Published inTDS ArchiveLinear Regression With BootstrappingThere were others who had forced their way to the top from the lowest rung by the aid of their bootstrapsMar 13, 20212Mar 13, 20212
Published inTDS ArchiveMultivariant Linear RegressionOh boy, homoscedasticity!Mar 12, 2021Mar 12, 2021
