Congrats—your model is live! But here’s the real question: How do you keep it learning, improving, and actually useful? In this talk, I’ll explain how to build an MLOps pipeline from scratch, making sure your model doesn’t just sit there gathering dust.

We’ll cover:
🔥 Setting up CI/CD/CT for ML without losing your mind
🔥 Model versioning & storage (because you don’t want to lose track of what’s running)
🔥 How to automate continuous training with Ray + GCP like a pro
🔥 Keeping everything smooth with minimal risk & max efficiency

If you're into making ML actually work in production, this one’s for you. Let’s get your models learning on autopilot. 🚀