Practice Backpropagation Algorithm (7.3.1) - Deep Learning and Neural Networks

Practice: Backpropagation Algorithm

Lesson 7.3.1Deep Learning and Neural Networks

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9 questions

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6 sample questions

Question 1.
What is the first step of the backpropagation algorithm?
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Think about what happens when the data first enters the neural network.
Question 2.
What does a loss function do?
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Consider how we assess our model's predictions.
3Question 3.
What is the purpose of backpropagation?
- To compute outputs
- To minimize loss
- To adjust learning rate
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Remember the role of backpropagation in the training cycle.
4Question 4.
True or False: The loss function is calculated during the backward pass.
- True
- False
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Consider when in the process we discuss outputs and losses.
Question 5.
Consider a neural network with an unexpected spike in loss after several epochs of training. Discuss the possible causes and how backpropagation may be adapted to address this issue.
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Think about how various parameters can affect network behavior.
Question 6.
Explain how backpropagation would need to change if you were to implement it on a network with recurrent connections, as seen in RNNs.
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Consider how feedback from one layer influences future inputs in RNNs.

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