<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Explainers on Shaun Yap</title><link>https://shaunyap01.github.io/explainers/</link><description>Recent content in Explainers on Shaun Yap</description><generator>Hugo -- 0.128.0</generator><language>en</language><lastBuildDate>Mon, 04 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://shaunyap01.github.io/explainers/index.xml" rel="self" type="application/rss+xml"/><item><title>Bayesian Inference: A Statistician's Explainer</title><link>https://shaunyap01.github.io/explainers/bayesian-inference/bayesian-inference/</link><pubDate>Mon, 04 May 2026 00:00:00 +0000</pubDate><guid>https://shaunyap01.github.io/explainers/bayesian-inference/bayesian-inference/</guid><description>A comprehensive, intuitive, and mathematically rigorous guide to Bayesian inference. We break down Bayes&amp;#39; theorem, priors, likelihoods, and posteriors, exploring how this probabilistic framework fundamentally changes the way we learn from data.</description></item></channel></rss>