Data Augmentation Techniques in CNN
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Questions and Answers

What is the primary goal of regularization in deep learning models?

  • Improve the model's ability to generalize
  • Speed up the training process
  • Remove less important patterns in the data (correct)
  • Increase the number of non-zero parameters

    • What is the main benefit of using parameter sharing in convolutional neural networks?

  • Learning characteristics in many local positions of data (correct)
  • Reducing the number of parameters
  • Increasing the depth of the neural network
  • Improving the model's ability to generalize

    • What is the primary advantage of using early stopping in gradient descent?

  • Preventing overfitting (correct)
  • Improving the model's ability to generalize
  • Speeding up the training process
  • Reducing the number of parameters

    • What is the consequence of increasing the depth of a neural network?

    <p>Reducing the number of parameters</p> Signup and view all the answers

    What is the purpose of data augmentation in deep learning?

    <p>Changing the sample data slightly every time the model processes it</p> Signup and view all the answers

    What is the main advantage of using ensemble methods in deep learning?

    <p>Obtaining an additional accuracy improvement</p> Signup and view all the answers

    What is the consequence of the vanishing and exploding gradient problems in deep neural networks?

    <p>The updated value can either be small or increasingly large</p> Signup and view all the answers

    What is one solution to the vanishing and exploding gradient problems in deep neural networks?

    <p>Using ReLU activation function</p> Signup and view all the answers

    What is the main advantage of using convolutional neural networks for image recognition tasks?

    <p>Learning characteristics in many local positions of data</p> Signup and view all the answers

    What is the purpose of trading off breadth for depth in deep neural networks?

    <p>Turning out the neural network with more layers</p> Signup and view all the answers

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