@Bayes’ Theorem For Bae
Author(s): Michael Knight Originally published on Towards AI. Intro to Probability and Stats U+007C Towards AI Introduce someone to probability theory and statistics without scaring them off Source Bayes’ Theorem is something that confuses and frustrates many, but is not as awful …
An Intro to Pymc and the Language for Describing Statistical Models
Author(s): Ruiz Rivera Originally published on Towards AI. Photo by Paul Nicklen on Treehugger In our previous article on why most examples of Bayesian inference misrepresent what it is, we clarified a common misunderstanding among beginners of Bayesian Statistics. That is, the …
Probability theory: Explaining prediction of uncertainty
Author(s): Abhijith S Babu Originally published on Towards AI. Our future, as we all know, is uncertain. Using the techniques available right now, it is nearly impossible to predict the future. But we still make plans for the future, assuming things will …
Probability Theory: Explaining Prediction of Uncertainty
Author(s): Abhijith S Babu Originally published on Towards AI. Our future, as we all know, is uncertain. Using the techniques available right now, it is nearly impossible to predict the future. But we still make plans for the future, assuming things will …
Growing Teeth
Author(s): Dr. Marc Jacobs Originally published on Towards AI. Bayesian analysis of the Teeth Growth dataset. To show that Bayesian analysis is really not that difficult, or far from how we humans deal with (new) information, I have posted several Bayesian analyses …
Introduction to Bayesian Inference
Author(s): ___ Originally published on Towards AI. A Distribution With No Constraints Top highlight In this article, I will explain what the maximum entropy principle is, how to apply it and why it’s useful in the context of Bayesian inference. The code …
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