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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the first step of the backpropagation algorithm?
💡 Hint: Think about what happens when the data first enters the neural network.
Question 2
Easy
What does a loss function do?
💡 Hint: Consider how we assess our model's predictions.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the purpose of backpropagation?
- To compute outputs
- To minimize loss
- To adjust learning rate
💡 Hint: Remember the role of backpropagation in the training cycle.
Question 2
True or False: The loss function is calculated during the backward pass.
- True
- False
💡 Hint: Consider when in the process we discuss outputs and losses.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
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.
💡 Hint: Think about how various parameters can affect network behavior.
Question 2
Explain how backpropagation would need to change if you were to implement it on a network with recurrent connections, as seen in RNNs.
💡 Hint: Consider how feedback from one layer influences future inputs in RNNs.
Challenge and get performance evaluation