Open b0c1 opened 8 years ago
It looks like perceptron in synaptic
corresponds to one Sequental
layer in leaf
that itself consists from 3 layers: 1) Linear
, 2) Sigmoid
or ReLU
, 3) another Linear
.
Currently Leaf supports feedforward networks and AFAIK only them. Here is an example.
Supporting @alexandermorozov's answer:
Feedforward networks are built with a Sequential
layer in Leaf. The Sequential
layer can use any kind of layer, even other Sequential
layers. The API in Leaf is very, very easy. I would say even easier than the synaptic one.
There is currently a PR for the Leaf Book #93 which has all the chapters by now, although there are still a lot of grammar, spelling mistakes - clean up is on the way. The Leaf Book will also have a Glossary, I will use your input of neurons/perceptrons/etc. If there are some other confusions or if you would like to clarify the confusion a bit more, I would be pleased about a comment at #93
Hi guys, I'm a little confused. I'm a beginner in neural networks but some docs/library use neuron/preceptron/etc (like http://synaptic.juancazala.com/ ) some using layer/solver (leaf). What's the difference? Can I write a feedforward network in leaf? (like http://synaptic.juancazala.com/#/paint-an-image )