TensorBoard is TensorFlow's visualization tool, which can be used to visualize a computational graph. It can also be used to plot various quantitative metrics and the results of several intermediate calculations. When we are training a really deep neural network, it becomes confusing when we have to debug the network. So, if we can visualize the computational graph in TensorBoard, we can easily understand such complex models, debug them, and optimize them. TensorBoard also supports sharing.
As shown in the following screenshot, the TensorBoard panel consists of several tabs—SCALARS, IMAGES, AUDIO, GRAPHS, DISTRIBUTIONS, HISTOGRAMS, and EMBEDDINGS:
The tabs are pretty self-explanatory. The SCALARS tab shows useful information about the scalar variables we use in our program. For example, it shows how the value of a scalar variable called loss...
