Bayesian Analysis with Python

Summary

We learned that linear regression is one of the most widely used models in statistics and machine learning and it is also the building block of several more complex methods. This is a widely used model and different people tend to give different names to the same concept or object. Thus, we first introduced some commonly used vocabulary in statistics and machine learning. We studied the core of the linear model, an expression to connect an input variable to an output variable. In this chapter, we performed that connection using Gaussian and Student's t-distributions and in future chapters we will extend this model to other distributions. We dealt with computational problems and how to fix them by centering and/or standardizing the data ...