There are 40 nodes that can be used as successor
for a node with an output port of type TensorFlow 2 Model.
Simple RNN layer.
Allows custom editing of a (Python compatible) deep learning network in a local Python installation.
Allows custom execution of a (Python compatible) deep learning network in a local Python installation.
Allows custom training and fine-tuning/transfer learning of a (Python compatible) deep learning network in a local Python installation.
The loop end node for an active learning loop.
The loop start node for an active learning loop.
Executes a TensorFlow deep learning network.
Writes a TensorFlow 2 Network to a file or directory.
Executes a deep learning network.
Run R code with a pre-trained R model on a Microsoft SQL Server in a database.