Posted by Gal Oshri , Product Manager TensorBoard , TensorFlow’s visualization toolkit, is often used by researchers and engineers to visualize and understand their ML experiments. It enables tracking experiment metrics , visualizing models , profiling ML programs , visualizing hyperparameter tuning experiments , and much more.
We have seen people sharing screenshots of their TensorBoards to achieve this. However, screenshots aren’t interactive and fail to capture all the details. At Google, researchers and engineers often communicate their insights about model behavior by sending their TensorBoard visualizations to teammates. Our goal is to provide this capability to the broader community.
Source: Introducing TensorBoard.dev: a new way to share your ML experiment results