Do you think it's the best approach to construct and train a simple DCNN in tensorflow and then run the trained NN with convnetjs in a JS app?
Basically, I'm writing a tsumego solver in JS and recently I've found a paper that describes promising results in application of NNs to tsumego solving. I want to replicate that NN, train on my data, make a couple improvements and use in my solver.
TF is supposed to be very fast as it uses C++ back-end with state-of-the-art (I hope) matrix-related and other algorithms. However somewhere on stackoverflow people claimed that convnetjs is way faster despite it's in JS. I'm a newbie in machine learning (still completing the TF tutorial), hence asking.
Hi Andrew,
Do you think it's the best approach to construct and train a simple DCNN in tensorflow and then run the trained NN with convnetjs in a JS app?
Basically, I'm writing a tsumego solver in JS and recently I've found a paper that describes promising results in application of NNs to tsumego solving. I want to replicate that NN, train on my data, make a couple improvements and use in my solver.
TF is supposed to be very fast as it uses C++ back-end with state-of-the-art (I hope) matrix-related and other algorithms. However somewhere on stackoverflow people claimed that convnetjs is way faster despite it's in JS. I'm a newbie in machine learning (still completing the TF tutorial), hence asking.
Regards.