Bayesian Thinking & Estimating Posterior Distribution for Linear Regression @ Data Ketchup…

One of the major motivations of this research is the fact that there has been an increasing focus on Deep model interpretability with the advent of more and more complex models. More is the complexity of the model, difficult it gets to have interpretability with respect to the outputs and a lot of research is going in the field of Bayesian thinking and learning. But before understanding and being able to appreciate Bayesian in deep neural models, we should be well versed and adept with Bayesian thinking in linear models for example- Bayesian Linear regression. But there are very few good materials available online in a combined fashion which can give a clear motivation and understanding of the Bayesian Linear regression. This was one of the major motivations for this blog and here I will try to give an understanding of how to approach the Linear regression from a Bayesian analysis standpoint.