<?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>Model Evaluation on Code by Night Learning to Program Journey Log</title><link>https://codebynight.dev/tags/model-evaluation/</link><description>Recent content in Model Evaluation on Code by Night Learning to Program Journey Log</description><image><title>Code by Night Learning to Program Journey Log</title><url>https://codebynight.dev/images/preview.png</url><link>https://codebynight.dev/images/preview.png</link></image><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 20 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://codebynight.dev/tags/model-evaluation/index.xml" rel="self" type="application/rss+xml"/><item><title>Why Data Scientists Keep Saying Not To Use Prophet</title><link>https://codebynight.dev/posts/why-data-scientists-are-skeptical-of-prophet-forecasts/</link><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><guid>https://codebynight.dev/posts/why-data-scientists-are-skeptical-of-prophet-forecasts/</guid><description>I tested Prophet against seasonal naive and ETS on two monthly series to see why a clean forecast chart is not enough to trust the model.</description></item></channel></rss>