from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD
import numpy as np
X = np.array([[0,0],[0,1],[1,0],[1,1]])
y = np.array([[0],[1],[1],[0]])
model = Sequential()
model.add(Dense(8, input_dim=2))
model.add(Activation('tanh'))
model.add(Dense(1))
model.add(Activation('sigmoid'))
sgd = SGD(lr=0.1)
model.compile(loss='binary_crossentropy', optimizer=sgd)
model.fit(X, y, batch_size=1, epochs=1000, verbose= 0)
print(model.predict_proba(X))
model.save('saved_model/keras.h5')
!pip install tensorflowjs
!tensorflowjs_converter --input_format keras saved_model/keras.h5 web_model
header = '\n'
script = '\
\n\
\n'
body = '\
\n\
\n\
'
with open('index.html','w') as f:
f.write(header+script+body)
f.close()