Professional Courses
Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.
Categories
Interactive Games
Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.
Typing
Memory
Math
English Adventures
Knowledge
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the purpose of dropout in neural networks?
💡 Hint: Think about how it affects neuron collaboration.
Question 2
Easy
Define L1 regularization.
💡 Hint: Consider the effect on model complexity.
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 does dropout do in a neural network?
- A) Increases the number of neurons
- B) Randomly disables neurons during training
- C) Reduces the training set size
💡 Hint: Consider its role in preventing overfitting.
Question 2
True or False: L2 regularization always sets weights to zero.
- True
- False
💡 Hint: Think about the nature of the L2 penalty.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
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.
Question 2
Evaluate the impact of setting a high penalty in L1 regularization on specific types of datasets.
💡 Hint: Reflect on model interpretability versus complexity.
Challenge and get performance evaluation