Practice Components of a Neuron (Perceptron) - 8.3 | 8. Neural Network | CBSE Class 11th AI (Artificial Intelligence)
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8.3 - Components of a Neuron (Perceptron)

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is represented by the inputs in a perceptron?

💡 Hint: Think about what data characteristics might influence the prediction.

Question 2

Easy

What does a weight determine in a perceptron?

💡 Hint: Consider how different inputs may have different levels of significance.

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 purpose of weights in a perceptron?

  • To store inputs
  • To normalize outputs
  • To determine input importance

💡 Hint: Consider how weights affect the computation.

Question 2

True or False: The output of the sigmoid function is always greater than or equal to 0.

  • True
  • False

💡 Hint: Think about the range of outputs for the sigmoid function.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given inputs [2, 4, 6], weights [0.5, 0.3, 0.2], and a bias of 2, compute the output of the perceptron's summation function. Then choose an activation function (either Sigmoid or ReLU) and explain how it transforms the output.

💡 Hint: Remember to apply the equation step by step!

Question 2

Create a perceptron model for predicting whether a fruit is an apple or not based depending on the attributes: weight (grams), sweetness (0-10), and color score (1-10). Explain how weights might be adjusted through learning.

💡 Hint: Consider how features might correlate to the classification.

Challenge and get performance evaluation