I can build a model that scores great on my own tests. But when it goes live and starts doing worse than it should, I'm lost, digging through data and numbers trying to figure out what changed. Knowing how to build one turned out to be a whole different skill from figuring out why it's quietly failing in the real world.
More people experience this than they realize.
You can build a working model, but figuring out why it underperforms in production still beats you.
If this sounds familiar, the Library can help you find the bigger picture.