diff --git a/brainage/neural_net.py b/brainage/neural_net.py
index 11a1a4e..406bd27 100644
--- a/brainage/neural_net.py
+++ b/brainage/neural_net.py
@@ -23,7 +23,7 @@ def create_nn(input_shape,
                   optimizer = 'rmsprop',
                   dropout = 0.05,
                   summary = False):
-   """
+    """
     Create a neural network model using Keras API in order to solve a regression problem.
 
     :param input_shape: shape of the data given to the input layer of the NN
@@ -67,7 +67,7 @@ def create_nn(input_shape,
     return model
 
 def training(features, targets, model, epochs, **kwargs):
-   """
+    """
     Train a neural network using k-fold cross-validation. 
     The function can show actual vs predicted brain age scatter plot and training history plot.
 
diff --git a/brainage/regression.py b/brainage/regression.py
index 931741f..b3b7fd7 100644
--- a/brainage/regression.py
+++ b/brainage/regression.py
@@ -121,7 +121,7 @@ def regression(type, features, targets, n_splits):
 
 
 def reg_parsing():
-     """
+    """
     regression function parsed that runs when the .py file is called.
     It performs regression (linear or gaussian) with k-fold cross-validation 
     predicting the age of patients from magnetic resonance imaging and
diff --git a/brainage/utils.py b/brainage/utils.py
index 523d200..b5638b2 100644
--- a/brainage/utils.py
+++ b/brainage/utils.py
@@ -37,7 +37,7 @@ def abs_path(local_filename, data_folder):
     return data_file_path
 
 def mean_spurious(df):
-   """
+    """
     Handles spurious 0 and -9999 values in the data, if the dataset is not properly cleaned before.
     This function will replace 0 and -9999 values with the mean of respective columns