Simple neural network example

#Initializing the neural network

model = Sequential()

model.add(Dense(1,input_dim=x_train.shape[1]))

model.summary()

optimizer = keras.optimizers.SGD()    # defining SGD as the optimizer to be used

model.compile(loss="mean_squared_error", optimizer=optimizer, metrics=metrics,run_eagerly=True)

epochs = 10

batch_size = x_train.shape[0]

start = time.time()

history = model.fit(x_train, y_train, validation_data=(x_val,y_val) , batch_size=batch_size, epochs=epochs)

end=time.time()

plot(history,'loss')

plot(history,'r2_score')

results.loc[0]=['-','-','-',epochs,batch_size,'GD',(end-start),history.history["loss"][-1],history.history["val_loss"][-1],history.history["r2_score"][-1],history.history["val_r2_score"][-1]]