Practice Types of Deep Learning Architectures - 8.5 | 8. Deep Learning and Neural Networks | Data Science Advance
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8.5 - Types of Deep Learning Architectures

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is a CNN designed for?

💡 Hint: Think about what kinds of data involve pixels.

Question 2

Easy

Give a main application of RNNs.

💡 Hint: Consider examples like predicting the next word in a sentence.

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 type of data do Convolutional Neural Networks (CNNs) primarily work with?

  • Time series data
  • Image and spatial data
  • Text data

💡 Hint: Think of applications involving pixels.

Question 2

True or False: Autoencoders are primarily used for supervised learning.

  • True
  • False

💡 Hint: Consider what type of labeling is needed for training.

Solve 3 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset of images, which deep learning architecture would you choose for classification tasks? Justify your choice.

💡 Hint: Think about what type of patterns CNNs are adept at recognizing.

Question 2

Explain how training a GAN differs from training a traditional neural network.

💡 Hint: Consider the interaction between the networks for learning.

Challenge and get performance evaluation