<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Sagemaker on Victoria Dyster, PhD</title><link>http://victoriadyster.com/tags/sagemaker/</link><description>Recent content in Sagemaker on Victoria Dyster, PhD</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 Victoria Dyster, PhD</copyright><lastBuildDate>Fri, 15 Nov 2024 00:00:00 +0000</lastBuildDate><atom:link href="http://victoriadyster.com/tags/sagemaker/index.xml" rel="self" type="application/rss+xml"/><item><title>Scaling ML Training for Epigenetic Age Prediction</title><link>http://victoriadyster.com/projects/epigenetic-age-prediction/</link><pubDate>Fri, 15 Nov 2024 00:00:00 +0000</pubDate><guid>http://victoriadyster.com/projects/epigenetic-age-prediction/</guid><description>How parallelising hyperparameter tuning on SageMaker turned a single-instance grid search into a 100x faster training workflow.</description></item></channel></rss>