The book is mostly focused on the mathematical foundations of these models as opposed to implementation in R or Python, but in this repository I have created Jupyter Notebooks with R code that gives examples of how to build multiple linear regression models, interpret the result, check model assumptions, perform transformations and interpret influential points. These essential data science tasks are worked through along side mathematical formulas in the notebooks to show the underlying maths of each step.
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