Most models don’t fail because of bad algorithms.
They fail because of bad data.
Common issues:
Inconsistent labeling
Weak QA
Missing edge cases
Good data = better models.
If you’re training models, data quality is everything.
One of the easiest pitfalls in tech is accidentally losing sight of the customer problem. Just figure out the customer problem and build the best solution. That’s it!
Treat yourself to a couple of minutes of feeling good. These babies are wearing hearing aids, and for the first time they're hearing what is being said to them.
“If you are irresponsible enough to think that you don’t mind if you get the flu, remember it’s not about you - it’s about everybody else.”
Intensive care specialist Professor Hugh Montgomery explains why this coronavirus is different from the ordinary flu.