Currently, I am implementing a two-part saving strategy where the keras part of the model is saved to h5, and the sklearn/umap part is saved as a pickle (or joblib maybe?) file, however I am sure this is not that convenient. If anybody would like to propose a more elegant way to save N2D objects for easy deployment, I am open to suggestions!
Currently, I am implementing a two-part saving strategy where the keras part of the model is saved to h5, and the sklearn/umap part is saved as a pickle (or joblib maybe?) file, however I am sure this is not that convenient. If anybody would like to propose a more elegant way to save N2D objects for easy deployment, I am open to suggestions!