Practice - Algorithmic Optimization
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Practice Questions
Test your understanding with targeted questions
Define model pruning.
💡 Hint: Think about what happens when you reduce the complexity of a network.
What is quantization?
💡 Hint: Consider the difference between 32-bit and 8-bit data types.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the main goal of algorithmic optimization?
💡 Hint: Think about efficiency in computations.
True or False: Model pruning increases the size of a neural network.
💡 Hint: Consider what pruning means.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Given a neural network with 1M weights, if applying model pruning reduces weights to 200K while maintaining 90% accuracy, discuss possible implications for deployment in edge devices.
💡 Hint: Consider factors like processing time and memory in edge applications.
Analyze the trade-offs involved with quantization in a deep learning model that previously used 32-bit floats. What are the possible impacts on performance and accuracy?
💡 Hint: Reflect on the effects of reduced precision on output.
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