In this section you will find documentation related to tools in the TensorFlow ecosystem.
Training Runs: The tfruns package provides a suite of tools for tracking and managing TensorFlow training runs and experiments from R. Track the hyperparameters, metrics, output, and source code of every training run, visualize the results of individual runs and comparisons between runs.
TensorBoard: The computations you’ll use TensorFlow for - like training a massive deep neural network - can be complex and confusing. To make it easier to understand, debug, and optimize TensorFlow programs, a suite of visualization tools called TensorBoard is available. You can use TensorBoard to visualize your TensorFlow graph, plot quantitative metrics about the execution of your graph, and show additional data like images that pass through it.