https://samarthya.me/tags/gcp/Recent content in Gcp on SamarthyaHugo -- gohugo.ioen© Samarthya 2018-2026. All rights reserved.Mon, 26 Oct 2026 18:10:00 -0400https://samarthya.me/posts/ai-in-practice-2-vertex-ai-pipelines/Mon, 26 Oct 2026 18:10:00 -0400https://samarthya.me/posts/ai-in-practice-2-vertex-ai-pipelines/<div class="lead text-neutral-500 dark:text-neutral-400 !mb-9 text-xl"> A notebook that trains a good model once is an experiment. A pipeline that trains it again next week, on new data, and tells you whether it got better: that&rsquo;s a system. Here&rsquo;s how Google&rsquo;s Vertex AI turns one into the other. </div> <h2 class="relative group">Why pipelines <div id="why-pipelines" class="anchor"></div> <span class="absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none"> <a class="text-primary-300 dark:text-neutral-700 !no-underline" href="#why-pipelines" aria-label="Anchor">#</a> </span> </h2> <p>Training a model is never one step. Data is extracted, cleaned and split; a model is trained, evaluated and compared with the current one; if it&rsquo;s better, it&rsquo;s registered and deployed. Done by hand in a notebook, that sequence is easy to get subtly wrong and impossible to audit.</p>