Machine learning models, especially deep learning ones, can be complex.

In this video from QCon.ai 2018, Chi Zeng walks us through how to debug, monitor, and examine the decisions of a TensorFlow-based model using the TensorBoard suite of visualizations.

Chi Zeng works on the TensorBoard suite of visualizations within Google Brain.

TensorBoard is a suite of visualization tools that make it easier to understand, debug, and optimize TensorFlow programs.

Developer Advocate Laurence Moroney speaks with Justine Tunney, the dev lead for TensorBoard, about how the debugger plugin gives you an x-ray into your models.