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4 cards from this section. Quick, good the night before a test.
What is the primary purpose of backpropagation in neural networks?
Think about how we improve our predictions.
What is gradient descent?
Consider it as a way to reach the lowest point.
What does backpropagation primarily aim to achieve in a neural network?
Think about what helps improve a model's predictions.
True or False: Backpropagation only occurs once during the training of a neural network.
Consider how often training happens in other contexts.
You have a neural network model that is consistently underperforming on validation data despite achieving a high accuracy on training data. Discuss how you could use backpropagation to improve the model. What strategies might you implement to combat overfitting?
Think about how overfitting manifests and consider structural changes to the model.
Consider a scenario where your learning rate is set too high. Describe the consequences and how you can identify that it's impacting the training of your neural network negatively.
Reflect on how learning rates affect gradual adjustments of weights.
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