8.4 - Regularization Techniques
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Practice Questions
Test your understanding with targeted questions
What is the purpose of dropout in neural networks?
💡 Hint: Think about how it affects neuron collaboration.
Define L1 regularization.
💡 Hint: Consider the effect on model complexity.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does dropout do in a neural network?
💡 Hint: Consider its role in preventing overfitting.
True or False: L2 regularization always sets weights to zero.
💡 Hint: Think about the nature of the L2 penalty.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Devise a plan to experimentally test the effectiveness of dropout vs. L2 regularization on the same dataset.
💡 Hint: Consider the models' architecture and validation metrics you will employ.
Evaluate the impact of setting a high penalty in L1 regularization on specific types of datasets.
💡 Hint: Reflect on model interpretability versus complexity.
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