I have a neural network model that is created in convnet.js that I have to define using Keras. Does anyone have an idea how can I do that?
neural = {
net : new convnetjs.Net(),
layer_defs : [
{type:'input', out_sx:4, out_sy:4, out_depth:1},
{type:'fc', num_neurons:25, activation:"regression"},
{type:'regression', num_neurons:5}
],
neuralDepth: 1
}
this is what I could do so far. I cannot ve sure if it's correct.
#---Build Model-----
model = models.Sequential()
# Input - Layer
model.add(layers.Dense(4, activation = "relu", input_shape=(4,)))
# Hidden - Layers
model.add(layers.Dense(25, activation = "relu"))
model.add(layers.Dense(5, activation = "relu"))
# Output- Layer
model.add(layers.Dense(1, activation = "linear"))
model.summary()
# Compile Model
model.compile(loss= "mean_squared_error" , optimizer="adam", metrics=["mean_squared_error"])
from Convert Convnet.js neural network model to Keras Tensorflow
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