Practice Challenges in Training - 8.3.3 | 8. Deep Learning and Neural Networks | Data Science Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the vanishing gradient problem?

💡 Hint: Think about how gradients affect learning.

Question 2

Easy

List one strategy to mitigate overfitting.

💡 Hint: Think about regularization techniques.

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 happens during the vanishing gradient problem?

  • Gradients become too small
  • Gradients become too large
  • Gradients are unaffected

💡 Hint: Remember how gradients affect learning.

Question 2

True or False: Overfitting leads to poor performance on training data.

  • True
  • False

💡 Hint: Consider the meaning of overfitting.

Solve 3 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design an experiment to measure the impact of dropout on a network's performance. What metrics will you use?

💡 Hint: Consider practical metrics that reflect training success.

Question 2

Discuss how computational complexity in deep learning might evolve with advancements in hardware technology. What could the future hold?

💡 Hint: Think about trends in technology and their implications.

Challenge and get performance evaluation