import numpy as np
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
train_x=np.arange(-20,20,0.25)
train_y=np.sqrt((2*train_x**2)+1)
model = Sequential()
model.add(Dense(8,input_dim=1,activation='relu')) # input hidden ke input
model.add(Dense(4, activation = 'relu')) # dim layer
model.add(Dense(1, activation = 'linear')) # ouput layer
model.compile (loss = 'mean_squared_error', optimizer = 'adam')
model.fit(train_x,train_y,batch_size=20, epochs=10000,verbose=2)
print(model.summary())
model.save("model.h5")
# test kasus
x=np.array([26])
predict= model.predict(x)
print("f(26) =", predict )
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