I am working on Google Tensorboard, and I\'m feeling confused about the meaning of Histogram Plot. I read the tutorial, but it seems unclear to me. I really appreciate if anyone
@marc_alain, you're a star for making such a simple script for TB, which are hard to find.
To add to what he said the histograms showing 1,2,3 sigma of the distribution of weights. which is equivalent to the 68th,95th, and 98th percentiles. So think if you're model has 784 weights, the histogram shows how the values of those weights change with training.
These histograms are probably not that interesting for shallow models, you could imagine that with deep networks, weights in high layers might take a while to grow because of the logistic function being saturated. Of course I'm just mindlessly parroting this paper by Glorot and Bengio, in which they study the weights distribution through training and show how the logistic function is saturated for the higher layers for quite a while.