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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the main limitation of linear functions in neural networks?
💡 Hint: Think about what simple straight lines can and cannot represent.
Question 2
Easy
Name one activation function used to introduce non-linearity.
💡 Hint: It’s a function used in neural networks!
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 primary function of non-linear activation functions?
- A. To ensure all outputs are linear
- B. To introduce non-linearity in models
- C. To limit the output range
💡 Hint: Think about what non-linear functions do compared to linear ones.
Question 2
True or False: Linear functions can effectively model complex relationships in data.
- True
- False
💡 Hint: Consider the nature of real-world data.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a simple neural network for a binary classification problem. Discuss how you would choose activation functions and why non-linearity is crucial in your design.
💡 Hint: Think about the role of non-linearity at each layer.
Question 2
Considering a dataset that exhibits a nonlinear relationship between its features and target variable, explain how you would confirm that your neural network is adequately capturing this relationship through its architecture.
💡 Hint: Consider ways to evaluate model performance and learning.
Challenge and get performance evaluation