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4 cards from this section. Quick, good the night before a test.
What is gradient descent?
Think about how the model learns from its mistakes.
Define overfitting.
Consider what happens if a student memorizes answers without understanding.
What is the purpose of gradient descent?
Think of this as finding the lowest point in a valley.
True or False: Backpropagation is an algorithm used to clean data before training.
Recall the role of backpropagation in training.
Given a dataset with high dimensions, outline a strategy to reduce the risk of overfitting when training a model.
Consider ways to simplify the model.
Suppose two models are trained with different learning rates. One has a high learning rate, and the other has a low learning rate. Predict the outcomes and justify your reasoning regarding convergence and model performance.
Think about how quickly or slowly adjustments are made during training.
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