Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is pruning in AI?
💡 Hint: Think about simplifying a complex structure.
Question 2
Easy
Name the two types of pruning discussed.
💡 Hint: One focuses on connections, the other on entire neurons.
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 main purpose of pruning in AI?
- To increase model size
- To remove unnecessary weights
- To add more nodes
💡 Hint: Think about what pruning does to complexity.
Question 2
True or False: Pruning may reduce the model's accuracy.
- True
- False
💡 Hint: What happens if essential components are removed?
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Consider a neural network composed of 10,000 weights. If 30% of its weights are pruned, what will be the new total number of weights? Discuss the potential implications of this pruning on computation.
💡 Hint: Think percentages here!
Question 2
Design an experiment to compare the effectiveness of weight pruning versus node pruning on a specific AI model. What metrics will you measure?
💡 Hint: What do you want to find out about each pruning effect?
Challenge and get performance evaluation