TL Model (Transfer Learning)



Transfer learning is the process of taking a pre-trained model (the weights and parameters of a network that has been trained on a large dataset by somebody else) and “fine-tuning” the model with a specified dataset. The idea is that the aforementioned pre-trained model will act as a feature extractor. TLModel node contains pre-trained Neural Network layers except for the last layer (output layer).

Since TLModel does not contain the last output layer, the dense layers usually are used with TLModel to create a complete deep learning model. The weights of the LTModel are locked down during the training.



List of pre-trained models

  • AlexNet_ImageNet_CNTK
  • ResNet18_ImageNet_CNTK
  • ResNet34_ImageNet_CNTK
  • ResNet50_ImageNet_CNTK
  • ResNet101_ImageNet_CNTK
  • ResNet152_ImageNet_CNTK
  • User_Defined_Model


Array of dimensions indicating the Input shape of the data used for the pre-trained model. This cannot be modified.