diff --git a/exploration/ml_pipeline_classification.py b/exploration/ml_pipeline_classification.py
index d1f7287..33d1125 100644
--- a/exploration/ml_pipeline_classification.py
+++ b/exploration/ml_pipeline_classification.py
@@ -15,15 +15,12 @@
 
 # %% jupyter={"source_hidden": true}
 # %matplotlib inline
-import datetime
-import importlib
 import os
 import sys
 
 import numpy as np
 import matplotlib.pyplot as plt
 import pandas as pd
-import seaborn as sns
 
 from sklearn import linear_model, svm, naive_bayes, neighbors, tree, ensemble 
 from sklearn.model_selection import LeaveOneGroupOut, cross_validate, StratifiedKFold
@@ -39,9 +36,6 @@ nb_dir = os.path.split(os.getcwd())[0]
 if nb_dir not in sys.path:
     sys.path.append(nb_dir)
 
-import machine_learning.labels
-import machine_learning.model
-
 # %% [markdown]
 # # RAPIDS models
 
diff --git a/exploration/ml_pipeline_classification_with_clustering.py b/exploration/ml_pipeline_classification_with_clustering.py
index 4ccea22..04c35aa 100644
--- a/exploration/ml_pipeline_classification_with_clustering.py
+++ b/exploration/ml_pipeline_classification_with_clustering.py
@@ -15,8 +15,6 @@
 
 # %% jupyter={"source_hidden": true}
 # %matplotlib inline
-import datetime
-import importlib
 import os
 import sys
 
@@ -29,10 +27,6 @@ from scipy import stats
 from sklearn.model_selection import LeaveOneGroupOut, cross_validate, StratifiedKFold
 from sklearn.impute import SimpleImputer
 
-from sklearn.dummy import DummyClassifier
-from sklearn import linear_model, svm, naive_bayes, neighbors, tree, ensemble
-from lightgbm import LGBMClassifier
-import xgboost as xg 
 
 from sklearn.cluster import KMeans
 
@@ -43,8 +37,6 @@ nb_dir = os.path.split(os.getcwd())[0]
 if nb_dir not in sys.path:
     sys.path.append(nb_dir)
 
-import machine_learning.labels
-import machine_learning.model
 from machine_learning.classification_models import ClassificationModels
 
 # %% [markdown]
diff --git a/exploration/ml_pipeline_classification_with_clustering_2_class.py b/exploration/ml_pipeline_classification_with_clustering_2_class.py
index 36468fa..3442733 100644
--- a/exploration/ml_pipeline_classification_with_clustering_2_class.py
+++ b/exploration/ml_pipeline_classification_with_clustering_2_class.py
@@ -15,26 +15,18 @@
 
 # %% jupyter={"source_hidden": true}
 # %matplotlib inline
-import datetime
-import importlib
 import os
 import sys
 
 import numpy as np
 import matplotlib.pyplot as plt
 import pandas as pd
-import seaborn as sns
 from scipy import stats
 
-from sklearn.model_selection import LeaveOneGroupOut, cross_validate, train_test_split
+from sklearn.model_selection import train_test_split
 from sklearn.impute import SimpleImputer
 from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
 
-from sklearn.dummy import DummyClassifier
-from sklearn import linear_model, svm, naive_bayes, neighbors, tree, ensemble
-from lightgbm import LGBMClassifier
-import xgboost as xg 
-
 from sklearn.cluster import KMeans
 
 from IPython.core.interactiveshell import InteractiveShell
@@ -44,8 +36,6 @@ nb_dir = os.path.split(os.getcwd())[0]
 if nb_dir not in sys.path:
     sys.path.append(nb_dir)
 
-import machine_learning.labels
-import machine_learning.model
 from machine_learning.classification_models import ClassificationModels
 
 # %% [markdown]