I agree, judgement comes from experience and hard to teach in a classroom setting. Judgement also improves when you make mistakes and learn from them over time :)
This is my favorite part: "Stage 2: Learning from Practice."
No matter what you are learning, you have to practice, make mistakes, and then make corrections. Fear of making mistakes is the failure, not the mistake itself.
Clear and solid breakdown, but here’s one thing nobody says out loud:
You can go through all three stages and still not be good at ML.
Why? Because the missing fourth stage is rarely taught:
Contextual Intelligence.
– When do you not use the model?
– What matters more than accuracy?
– Can you explain your output to someone who controls the budget?
Theory, practice, mistakes, they’re necessary.
But judgment is what turns skills into value. That’s the difference between an ML student and an ML operator.
I agree, judgement comes from experience and hard to teach in a classroom setting. Judgement also improves when you make mistakes and learn from them over time :)
This is my favorite part: "Stage 2: Learning from Practice."
No matter what you are learning, you have to practice, make mistakes, and then make corrections. Fear of making mistakes is the failure, not the mistake itself.
Thanks Dr. Susan! Loved it “Fear of making mistakes is the failure, not the mistake itself” :)