The platform includes a service for Tensorboard which is TensorFlow's visualization toolkit. In machine learning, to improve something you often need to be able to measure it. TensorBoard is a tool for providing the measurements and visualizations needed during the machine learning workflow. It enables tracking experiment metrics like loss and accuracy, visualizing the model graph, projecting embeddings to a lower dimensional space, and much more.
The platform writes the outputs of jobs in a TensorBoard log file, which allows you to view and compare results and neural networks.
You can create a Tensorboard service and must configure the following custom parameters: