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Linear RegressionCovers the concept of linear regression, including polynomial regression and hyperparameters selection.
Linear Regression BasicsIntroduces the basics of linear regression, covering OLS approach, residuals, hat matrix, and Gauss-Markov assumptions.
Regression: Interactive LectureCovers linear regression, weighted regression, locally weighted regression, support vector regression, noise handling, and eye mapping using SVR.
ANOVA: Partitioning Total SSCovers ANOVA method, focusing on partitioning total sum of squares into treatment and error components, mean square calculations, Fisher statistic, and F-distribution.