Bayesian Inference — Intuition and Example

with Python Code

Why did someone need to invent the Bayesian Inference?

In a nutshell, Bayesian inference was invented to update probability as we gather more data.

The essence of Bayesian Inference is to combine two different distributions (likelihood and prior) into one “smarter” distribution (posterior). The posterior is considered “smarter” because, unlike classic maximum likelihood estimation (MLE), it takes into account the prior. Once we calculate the…