diff --git a/utils_ml.py b/utils_ml.py
index 3222188..4dbdbc9 100644
--- a/utils_ml.py
+++ b/utils_ml.py
@@ -28,7 +28,7 @@ import warnings
 
 
 def load_train_test(type_of_activity, type_of_model):
-    BUCKET = f"projet-bdc2324-team1/Generalization_v2/{type_of_activity}"
+    BUCKET = f"projet-bdc2324-team1/1_Temp/1_0_Modelling_Datasets/{type_of_activity}"
     File_path_train = BUCKET + "/Train_set.csv"
     File_path_test = BUCKET + "/Test_set.csv"
     
@@ -52,7 +52,7 @@ def save_file_s3(File_name, type_of_activity, type_of_model, model):
     image_buffer = io.BytesIO()
     plt.savefig(image_buffer, format='png')
     image_buffer.seek(0)
-    FILE_PATH = f"projet-bdc2324-team1/{type_of_model}/{type_of_activity}/{model}/"
+    FILE_PATH = f"projet-bdc2324-team1/2_Output/2_1_Modeling_results/{type_of_model}/{type_of_activity}/{model}/"
     FILE_PATH_OUT_S3 = FILE_PATH + File_name + type_of_activity + '_' + model + '.png'
     with fs.open(FILE_PATH_OUT_S3, 'wb') as s3_file:
         s3_file.write(image_buffer.read())
@@ -61,16 +61,16 @@ def save_file_s3(File_name, type_of_activity, type_of_model, model):
 
 def save_result_set_s3(result_set, File_name, type_of_activity, type_of_model, model=None, model_path=False):
     if model_path:
-        FILE_PATH_OUT_S3 = f"projet-bdc2324-team1/{type_of_model}/{type_of_activity}/{model}/" + File_name + '.csv'
+        FILE_PATH_OUT_S3 = f"projet-bdc2324-team1/2_Output/2_1_Modeling_results/{type_of_model}/{type_of_activity}/{model}/" + File_name + '.csv'
     else:
-        FILE_PATH_OUT_S3 = f"projet-bdc2324-team1/{type_of_model}/{type_of_activity}/" + File_name + '.csv'
+        FILE_PATH_OUT_S3 = f"projet-bdc2324-team1/2_Output/2_1_Modeling_results/{type_of_model}/{type_of_activity}/" + File_name + '.csv'
     with fs.open(FILE_PATH_OUT_S3, 'w') as file_out:
         result_set.to_csv(file_out, index = False)
 
 
 def save_model_s3(File_name, type_of_activity, type_of_model, model, classifier):
     model_bytes = pickle.dumps(classifier)
-    FILE_PATH_OUT_S3 = f"projet-bdc2324-team1/{type_of_model}/{type_of_activity}/{model}/" + File_name + '.pkl'
+    FILE_PATH_OUT_S3 = f"projet-bdc2324-team1/2_Output/2_1_Modeling_results/{type_of_model}/{type_of_activity}/{model}/" + File_name + '.pkl'
     with fs.open(FILE_PATH_OUT_S3, 'wb') as f:
         f.write(model_bytes)
     
diff --git a/utils_stat_desc.py b/utils_stat_desc.py
index 681e623..471fe19 100644
--- a/utils_stat_desc.py
+++ b/utils_stat_desc.py
@@ -50,7 +50,6 @@ def load_files(nb_compagnie):
         df_campaigns_kpi["customer_id"]= directory_path + '_' +  df_campaigns_kpi['customer_id'].astype('str') 
         df_customerplus_clean["customer_id"]= directory_path + '_' +  df_customerplus_clean['customer_id'].astype('str') 
         df_products_purchased_reduced["customer_id"]= directory_path + '_' +  df_products_purchased_reduced['customer_id'].astype('str') 
-<<<<<<< HEAD
         
     # Remove companies' outliers
         df_tickets_kpi = remove_outlier_total_amount(df_tickets_kpi)
@@ -59,11 +58,9 @@ def load_files(nb_compagnie):
         for dataset in [df_campaigns_brut, df_campaigns_kpi, df_customerplus_clean, df_target_information]:
             dataset = dataset[dataset['customer_id'].isin(customer_id)]
         
-=======
         df_target_KPI["customer_id"]= directory_path + '_' +  df_target_KPI['customer_id'].astype('str')
 
     
->>>>>>> main
     # Concaténation
         customer = pd.concat([customer, df_customerplus_clean], ignore_index=True)
         campaigns_kpi = pd.concat([campaigns_kpi, df_campaigns_kpi], ignore_index=True)
@@ -89,7 +86,7 @@ def save_file_s3(File_name, type_of_activity):
     image_buffer = io.BytesIO()
     plt.savefig(image_buffer, format='png')
     image_buffer.seek(0)
-    FILE_PATH = f"projet-bdc2324-team1/stat_desc/{type_of_activity}/"
+    FILE_PATH = f"projet-bdc2324-team1/2_Output/2_0_Descriptive_Statistics/{type_of_activity}/"
     FILE_PATH_OUT_S3 = FILE_PATH + File_name + type_of_activity + '.png'
     with fs.open(FILE_PATH_OUT_S3, 'wb') as s3_file:
         s3_file.write(image_buffer.read())