Practice Deep Neural Networks (11.2.2.1) - Representation Learning & Structured Prediction
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Deep Neural Networks

Practice - Deep Neural Networks

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the primary purpose of Deep Neural Networks?

💡 Hint: Think about how they process information.

Question 2 Easy

What is backpropagation?

💡 Hint: Consider how predictions improve over time.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does 'Deep' in Deep Neural Networks refer to?

Number of layers
Model size
Training data amount

💡 Hint: Think about how multi-layer architecture is defined.

Question 2

True or False: Backpropagation helps adjust weights based on previous predictions.

True
False

💡 Hint: Consider how models improve performance over iterations.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a simple deep neural network architecture suited for classifying images of cats and dogs. Explain your choices for the number of layers and the type of activation functions.

💡 Hint: Consider image complexity and output requirements.

Challenge 2 Hard

Critically analyze the impact of batch size on the training of deep neural networks. Discuss how different batch sizes can affect convergence and generalization.

💡 Hint: Reflect on the advantages and drawbacks of both extremes.

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Reference links

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