Deep Learning Patterns and Practices

11 Transfer learning

This chapter covers

• Using prebuilt and pretrained models from TF.Keras and TensorFlow Hub
• Performing transfer learning between tasks in similar and distinct domains
• Initializing models with domain-specific weights for transfer learning
• Determining when to reuse high-dimensionality or low-dimensionality latent space

TensorFlow and TF.Keras support a wide availability of prebuilt and pretrained models. Pretrained models can be used as is, while prebuilt models can be trained from scratch. By replacing the task group, pretrained models can also be reconfigured to perform any number of tasks. The process of replacing or reconfiguring the task group with retraining is called transfer learning.

In essence, transfer learning ...