Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does RNN stand for?
π‘ Hint: Think about how it processes sequences.
Question 2
Easy
Name one application of LSTMs.
π‘ Hint: Consider where language or sequential data is involved.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does RNN stand for?
π‘ Hint: It's about how the network 'repeats' over time.
Question 2
True or False: LSTMs are better than RNNs at handling long sequences.
π‘ Hint: Consider what happens to memory in RNNs.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
Given a long sequence input, describe how an LSTM would process the information and retain crucial details relevant for tasks such as translation.
π‘ Hint: Break down the role of each gate.
Question 2
How would you modify a neural network model that is currently using only RNN for a long sequence prediction task to improve its performance?
π‘ Hint: Think about the characteristics that LSTMs provide.
Challenge and get performance evaluation