We spent three weeks building an image classifier.

A neural network beat us in one afternoon.

It was honestly a little insulting.

In this episode, we break down the brutal trade-off nobody puts in the headline.

Machine learning tells you why it decided.

Deep learning tells you what it decided.

A bank needs the why.

A startup needs the what.

We look at 60,000 images, 20% dropout layers, and why picking the wrong architecture costs you trust.

Stop optimizing for accuracy before you know who reads the output.