docs: update method name

README.md

@@ -115,7 +115,7 @@ def piven_model(input_size, hidden_units):
 ```
 
 The most straightforward way of running your Model is to subclass the `PivenBaseModel` class. This requires you
-to define a `build_model()` method in which you can add preprocessing pipelines etc. 
+to define a `build()` method in which you can add preprocessing pipelines etc. 
 
 ```python
 from piven.models.base import PivenBaseModel
@@ -125,7 +125,7 @@ from sklearn.preprocessing import StandardScaler
 
 
 class MyPivenModel(PivenBaseModel):
-    def build_model(self, build_fn = piven_model):
+    def build(self, build_fn = piven_model):
         model = PivenKerasRegressor(build_fn=build_fn, **self.params)
         # Finally, normalize the output target
         self.model = PivenTransformedTargetRegressor(