Practice Hidden Layers - 10.2.2 | 10. Introduction to Neural Networks | CBSE Class 12th AI (Artificial Intelligence)
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the role of hidden layers in a neural network?

💡 Hint: Think about how they connect inputs and outputs.

Question 2

Easy

Name one common activation function used in hidden layers.

💡 Hint: This function allows only positive values to pass through.

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 do hidden layers in a neural network primarily do?

  • Connect input and output layers
  • Perform complex computations
  • Store data

💡 Hint: Consider their function within the network.

Question 2

True or False: The activation function's primary role is to add linearity to the model.

  • True
  • False

💡 Hint: Think about the properties of activation functions.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Calculate how many neurons are needed if you have 5 inputs, 10 neurons in the first hidden layer, and 7 in the output layer, considering each hidden layer needs connections to all neurons.

💡 Hint: Consider how each layer connects to the next.

Question 2

Describe a scenario where using a deeper network with more hidden layers may lead to better model performance. Include potential drawbacks.

💡 Hint: Think about the balance between complexity and data overfitting.

Challenge and get performance evaluation