Practice Forward Propagation - 7.3 | 7. Deep Learning & Neural Networks | Advance Machine Learning
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7.3 - Forward Propagation

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the main purpose of forward propagation in a neural network?

πŸ’‘ Hint: Think about how inputs are processed.

Question 2

Easy

What operation is commonly used for computing the weighted sum in forward propagation?

πŸ’‘ Hint: Consider how we handle multiple inputs and weights.

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 role of forward propagation?

  • To calculate gradients
  • To compute outputs
  • To optimize weights

πŸ’‘ Hint: Think about what happens during the forward pass.

Question 2

True or False: Activation functions are not necessary for neural networks.

  • True
  • False

πŸ’‘ Hint: Think about the limitations of linear models.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Consider a neural network with two input nodes feeding into one hidden layer with three neurons. The input values are [1, 2] and the corresponding weights for each connection from input to hidden layer are given as [[0.1, 0.2], [0.3, 0.4]]. Compute the output of each hidden neuron if a ReLU activation function is used.

πŸ’‘ Hint: Calculate the weighted sums first, then apply the ReLU function.

Question 2

Given a batch of inputs [2, -1, 0], weights [[0.5, -0.2, 0.1], [-0.6, 0.4, 0.2]], and biases [0.3, 0.1], calculate the pre-activation output for each neuron in the layer after forward propagation.

πŸ’‘ Hint: Remember to add the corresponding bias after computing the weighted sums.

Challenge and get performance evaluation