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Bayesian Regression in R

===== Likes: 175 👍: Dislikes: 9 👎: 95.109% : Updated on 01-21-2023 11:57:17 EST ===== This is an alternative to the frequentist approach of machine learning. Bayesian incorporates human intuition and training a model does not require a lot of data. This is an incredible method and is often overlooked by more popular machine learning methods that require lots of data. Fun fact: If you have an 'infinite' amount of data, then your Bayesian Results will approach that of Ordinary Least Squares. Github for code: https://github.com/SpencerPao/Data_Sc... Full Conditionals https://bragqut.files.wordpress.com/2... Additional Stan Model output explanations https://m-clark.github.io/easy-bayes/... 0:00 - What is Bayesian Regression? 1:30 - Why should you use Bayesian Regression? 2:35 - Bayesian Regression Equation 3:32 - Theory behind Gibbs Sampler (MCMC) 4:05 - Understanding and preparing data for Bayesian Analysis 7:02 - Designing Gibbs Sampler (MCMC) 12:10 - Accuracy, Burn-in, Convergence, Confidence Intervals, Predictions 17:23 - rstanarm library