<?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>Posts on Being Mas</title><link>https://beingmas.com/posts/</link><description>Recent content in Posts on Being Mas</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 28 Jul 2026 22:07:50 -0400</lastBuildDate><atom:link href="https://beingmas.com/posts/index.xml" rel="self" type="application/rss+xml"/><item><title>ES100 Analysis 2026</title><link>https://beingmas.com/posts/es100-analysis-2026/</link><pubDate>Tue, 28 Jul 2026 22:07:50 -0400</pubDate><guid>https://beingmas.com/posts/es100-analysis-2026/</guid><description>&lt;p&gt;A few years ago, I embarked on a journey to earn a Masters in Data Science. I successfully did so and graduated from the University of Michigan, which I am quite proud of; however, one downside from that journey was my final project. I had hoped to focus on a passion project of mine, which is trail running, and specifically &lt;a href="https://easternstates100.com"&gt;Eastern States 100&lt;/a&gt;. I didn&amp;rsquo;t get enough traction from other classmates, nor was it permitted to take on a solo project, which I understood. So I took on the task of building out a machine learning pipeline and modeling aid station arrival times as a challenge for myself. What follows is the first part of that pipeline, which is the data ingestion, cleaning, and dashboard, which serves as a key deliverable for those participating in the Eastern States 100 race.&lt;/p&gt;</description></item></channel></rss>