Sha256: cfa120f39f831534c657115d5512331b92ed37141c6b9c7830e12ab966bd9d5c
Contents?: true
Size: 455 Bytes
Versions: 29
Compression:
Stored size: 455 Bytes
Contents
require "dnn" include Numo include DNN::Layers include DNN::Activations include DNN::Optimizers Model = DNN::Model x = SFloat[[0, 0], [1, 0], [0, 1], [1, 1]] y = SFloat[[0], [1], [1], [0]] model = Model.new model << InputLayer.new(2) model << Dense.new(16) model << ReLU.new model << Dense.new(1) model << SigmoidWithLoss.new model.compile(SGD.new) model.train(x, y, 20000, batch_size: 4, verbose: false) p model.predict(x)
Version data entries
29 entries across 29 versions & 1 rubygems