09. Dropout in Keras

Dropout

  1. Build from the previous network.
  2. Add a dropout layer after the pooling layer. Set the dropout rate to 50%.
  3. Make sure to note from the documentation above that the rate specified for dropout in Keras is the opposite of TensorFlow! TensorFlow uses the probability to keep nodes, while Keras uses the probability to drop them.

Workspace

This section contains either a workspace (it can be a Jupyter Notebook workspace or an online code editor work space, etc.) and it cannot be automatically downloaded to be generated here. Please access the classroom with your account and manually download the workspace to your local machine. Note that for some courses, Udacity upload the workspace files onto https://github.com/udacity , so you may be able to download them there.

Workspace Information:

  • Default file path:
  • Workspace type: jupyter
  • Opened files (when workspace is loaded): n/a

Next Concept