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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does ReLU stand for?
💡 Hint: Think about the shape of its graph.
Question 2
Easy
What range does the Sigmoid function output?
💡 Hint: Consider how it behaves at extreme inputs.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the primary purpose of using activation functions in neural networks?
💡 Hint: Consider what happens if there are no activation functions.
Question 2
The output range of the Tanh function is:
💡 Hint: Visualize their range on the graph.
Solve 2 more questions and get performance evaluation
Push your limits with challenges.
Question 1
Design a neural network architecture for a binary classification problem including how you would incorporate activation functions.
💡 Hint: Focus on the advantages of each activation function in context.
Question 2
Investigate a scenario using Tanh in a specific type of network architecture and justify its advantages over using ReLU.
💡 Hint: Reflect on handling sequential data and its requirements.
Challenge and get performance evaluation