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MLOps: Beyond Model Training - A Practical Guide

Two articles discuss MLOps, focusing on the practical aspects beyond initial model training. The first article emphasizes that building an MLOps platform is a significant undertaking, with training the model being only a fraction of the overall job. The second article provides a beginner's guide to MLOps, covering essential components like versioning, deployment, monitoring, and drift detection. AI

IMPACT These articles offer practical guidance for implementing and managing machine learning models in production environments.

RANK_REASON The articles provide commentary and guides on MLOps practices, not a new release or significant industry event.

Read on Medium — MLOps tag →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

MLOps: Beyond Model Training - A Practical Guide

COVERAGE [2]

  1. Medium — MLOps tag TIER_1 English(EN) · Aditi Ashok ·

    Training the Model Was Only 20% of the Job: Lessons from Building an MLOps Platform

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@aditiashok148/training-the-model-was-only-20-of-the-job-lessons-from-building-an-mlops-platform-14f12b41ef26?source=rss------mlops-5"><img src="https://cdn-images-1.medium.com/max/1774/1*uDwER…

  2. Medium — MLOps tag TIER_1 English(EN) · Mehmet Özel ·

    The Beginner MLOps Guide I Wish I Had — Versioning, Deployment, Monitoring, and Drift

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science-collective/the-beginner-mlops-guide-i-wish-i-had-versioning-deployment-monitoring-and-drift-4afc63afe22d?source=rss------mlops-5"><img src="https://cdn-images-1.medium.com/max/1672…