Skip to content
#

keraspreprocessing

Here is 1 public repository matching this topic...

This tutorial demonstrates data augmentation: a technique to increase the diversity of your training set by applying random (but realistic) transformations, such as image rotation. You will learn how to apply data augmentation in two ways: Use the Keras preprocessing layers, such as tf. keras.

  • Updated Mar 6, 2022
  • Jupyter Notebook

Add this topic to your repo

To associate your repository with the keraspreprocessing topic, visit your repo's landing page and select "manage topics."

Learn more