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Exercise

Adding dropout to your network

Dropout is a form of regularization that removes a different random subset of the units in a layer in each round of training. In this exercise, we will add dropout to the convolutional neural network that we have used in previous exercises:

  1. Convolution (15 units, kernel size 2, 'relu' activation)
  2. Dropout (20%)
  3. Convolution (5 units, kernel size 2, 'relu' activation)
  4. Flatten
  5. Dense (3 units, 'softmax' activation)

A Sequential model along with Dense, Conv2D, Flatten, and Dropout objects are available in your workspace.

Instructions
100 XP
  • Add dropout applied to the first layer with 20%.
  • Add a flattening layer.