def tf_keras_model(data):
x, y = data
model = TfSequential()
model.add(TfDense(3, input_dim=4))
model.add(TfDense(1))
model.compile(loss="mean_squared_error", optimizer=TfSGD())
model.fit(x, y)
return model
def tf_keras_model(data):
x, y = data
model = TfSequential()
model.add(TfDense(3, input_dim=4))
model.add(TfDense(1))
model.compile(loss="mean_squared_error", optimizer=TfSGD(learning_rate=0.001))
model.fit(x.values, y.values)
return model
def tf_keras_model(data):
x, y = data
from tensorflow.keras.models import Sequential as TfSequential
from tensorflow.keras.layers import Dense as TfDense
model = TfSequential()
model.add(TfDense(3, input_dim=4))
model.add(TfDense(1))
model.compile(loss='mean_squared_error', optimizer='SGD')
model.fit(x, y)
return model
