How AI Actually Works (Under the Hood)
Lesson 4 of 6
0%Lesson 4
20 min
Training Data, Loss, and Gradient Descent (Plain English)
Quick Summary
Training data supplies examples, a loss function measures error, and gradient descent guides small weight updates. Together they define what the model is rewarded for learning.
What you will learn
- ·Explain the roles of training, validation, and test data
- ·Describe loss as a measurement of model error
- ·Use a plain-language analogy for gradient descent