Adding vignette for how to use applications in models #29
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This PR introduces a new vignette demonstrating how to perform transfer learning with Keras Applications. It provides a clear, end-to-end example of using a pre-trained model (like
ResNet50
) as a feature extractor within atidymodels
workflow.This documentation-driven approach was chosen over adding a new helper function to the API, as the existing framework is already sufficiently flexible. The goal is to empower users by clearly documenting this powerful and common pattern.
This addresses the documentation request in issue #28 .
Key Changes:
vignettes/applications.Rmd
: A new vignette that walks through using the Keras Functional API to add a new classification head to a frozen, pre-trained base model._pkgdown.yml
: Added the new "Transfer Learning" vignette to the "Guides" section of the documentation website's navigation bar.