Getting ready for Slack apocalypse.

I've made some visualization improvements for the neural network layer nodes in my visual programming system "code flow canvas". Nodes can now have meta information to show internal data which is stored on the node level that is not shown on the node itself. For the neural network nodes this are the weights and biases.

Also the structure of the neural network itself can be viewed in a scalable way instead of just the nodes on the canvas itself. And with scalable I mean not showing all the nodes, but only a max of 10 per layer and add smaller dots in between to illustrate that there are more nodes then just the max 10 that are shown per layer. The number of dots are different depending on the total node count to make it clear that layers differ in total node count.

You can see it here: youtu.be/dvZrWEz1W4k or try it yourself at demo.codeflowcanvas.io and select the neural network mnist training & testing example.