CHAPTER 03 / 06 · LEARN
See the layers at work.
Deep learning Applied AI Engineering
Neural systems transform input through layers. The important work is choosing a focused task, testing it and reporting limits.
What changes when the input, model or test case changes?
An illustrative image signal moves through the network toward a class prediction.
03 / THE PROCESS
From idea
to evidence.
Three connected moves explain the subject and the work that makes it reviewable.
A model card with results and limitations.
- 01 / INPUT
Define the task
Choose a narrow text or image question and a sensible measure of success.
WHAT YOU CAN SHOWTask and evaluation plan - 02 / REPRESENTATION
Adapt a model
Explore neural networks and transfer learning with a small, inspectable experiment.
WHAT YOU CAN SHOWTested classification example - 03 / OUTPUT
Describe the limits
Report the data used, results, mistakes and situations where the model should not be trusted.
WHAT YOU CAN SHOWModel card
THE PRACTICE
Make the work
inspectable.
The example is a way to explore the idea. Real project evidence should include what was tried, what was observed and what remains uncertain.
KEEP IN VIEW
What the visual
doesn’t prove.
Animated connections are a teaching diagram. They are not a literal view into a trained model.
ROLE CONNECTIONS
These directions use ideas from this subject within the Applied AI Engineering learning path.