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
Intermediate Content
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Training Data, Loss, and Gradient Descent (Plain English) is part of How AI Actually Works (Under the Hood) — an intermediate module. We keep these gated so we can save your progress, recommend next steps, and personalize the curriculum.
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