From Zero to MLOps Hero: Your First Steps in Building an MLOps Model as a Beginner

Just a few months ago, I was where you are — thrilled by the possibilities of machine learning (ML), yet overwhelmed by how to deploy a model into production. That’s when I stumbled upon the term “MLOps.” It’s like the best of both worlds — combining the power of machine learning with the discipline of DevOps. But, as exciting as it sounds, the real question is, “Where do I begin?”

If you’re in the same boat, you’re in the right place. In this guide, we’ll dive into MLOps from the ground up, and I’ll break it down in a simple, story-driven way. You’ll be ready to build your first MLOps model in no time. Grab your coffee, and let’s start this journey together!

You need to adapt to the future in a way to survive!

“Change before you have to.” — Jack Welch

Table of Contents:

1. Introduction
2. What Is MLOps, and Why Should You Care?
3. MLOps Implementation Levels — From Manual to Full Automation
4. Tools You Need to Build Your First MLOps Model
5. Building and Deploying Your First MLOps Model
6. Scaling with Docker and CI/CD Automation
7. Monitoring Your Model in Production
8. Conclusion

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