What is MLOps?
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What is MLOps?
MLOps, short for Machine Learning Operations, is a set of practices that aims to reliably and efficiently deploy and maintain machine learning models in production. It bridges the gap between model development (Data Scientists) and model deployment (Operations), emphasizing automation, monitoring, and collaboration throughout the entire machine learning lifecycle. Think of it as DevOps, but specifically tailored for the unique challenges of machine learning.
Free resources to learn What is MLOps?
- BookMLOps Engineering at Scale - Carl Osipov
- ArticleWhat is MLOps?
- ArticleMLOps Explained: A Deep Dive into Machine Learning Operations
- ArticleMachine Learning Operations (MLOps) For Beginners
- ArticleMLOps vs DevOps: Differences, Overlaps, and Use Cases
- ArticleMLOps: What It Is, Why It Matters, and How to Implement It
- VideoWhat is MLOps?
- VideoMLOps Explained - What It Is, Why You Need It and How It Works
More in stage 1: What is MLOps?
What is MLOps?: common questions
Can I learn What is MLOps? in Hindi?
This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain What is MLOps? in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.
Is this What is MLOps? tutorial for beginners?
It is lesson 1 of 62 in the free MLOps roadmap, in stage 1, What is MLOps?. If you are new to MLOps, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.