You’ve trained your first ML model—congrats!
But now comes the real challenge: how do you keep it learning, improving, and delivering value over time?

In this talk, I’ll walk you through building an end-to-end MLOps pipeline from scratch, ensuring your model doesn’t end up forgotten in a folder— or worse, in production without oversight.

We’ll dive into:
- Setting up CI/CD/CT for machine learning (without losing your mind)
- Managing model versions and storage (so you always know what’s running)
- Automating continuous training using Ray + GCP like a seasoned pro
- Running your pipeline with minimal risk and maximum efficiency

https://docs.google.com/presentation/d/14yaK_MTWiaR7lW0lgudrxuT3LQ6ExH0Ntad4RAQfRRw/edit?usp=sharing