Practice Deep Neural Networks (DNNs) - 8.2 | 8. Deep Learning and Neural Networks | Data Science Advance
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8.2 - Deep Neural Networks (DNNs)

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What defines a neural network as 'deep'?

💡 Hint: Think about how many layers separate the inputs from the outputs.

Question 2

Easy

Name one common loss function used in regression tasks.

💡 Hint: Consider what function measures the average squared difference.

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 makes a neural network 'deep'?

  • Having one hidden layer
  • Having multiple hidden layers
  • Having no hidden layers

💡 Hint: Consider the layers involved in processing the input.

Question 2

Is Mean Squared Error used for classification tasks?

  • True
  • False

💡 Hint: Think about the types of data being compared in classification.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Consider a DNN with multiple hidden layers. Discuss the potential trade-offs between having a very deep network versus a shallower one in terms of learning capacity and overfitting.

💡 Hint: Think about the relationship between complexity, performance, and risk of overfitting.

Question 2

Design a basic neural network for classifying images. Indicate which loss function you would select and justify your choice.

💡 Hint: Consider what type of data you're working with and what function will best evaluate your model's performance.

Challenge and get performance evaluation