We will cover models such as linear and logistic regression, KNN, decision trees and ensembling methods such as Random Forest and Boosting, and kernel methods such as SVM. Methods, theory, and ...

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

statistical models, regression and classification, inference, prediction, and bias-variance tradeoff, (2) multiple linear regression, including its assumptions, inference, data transformations, ...