Practice Deep Learning and Neural Networks - 8 | 8. Deep Learning and Neural Networks | Data Science Advance
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8 - Deep Learning and Neural Networks

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What are the three main layers in a neural network?

💡 Hint: Think about how the model receives input, processes it, and outputs a result.

Question 2

Easy

Name one common activation function.

💡 Hint: It helps determine the output of neurons.

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 does the Sigmoid function do?

  • Outputs values between -1 and 1
  • Squashes input to (0
  • 1)
  • Provides linear output

💡 Hint: Remember what happens to input values in the activation function.

Question 2

True or False: Dropout randomly turns off neurons during training to prevent overfitting.

  • True
  • False

💡 Hint: Think about how this method impacts learning.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

How would you implement dropout in a neural network, and what impact would it have on model performance?

💡 Hint: Consider how random removal helps combat overfitting.

Question 2

Consider a scenario where you notice the vanishing gradient problem in your deep learning model. What strategies might you employ to alleviate this issue?

💡 Hint: Think about how adjusting layers can affect gradient flow.

Challenge and get performance evaluation