Update app.py

app.py

@@ -6,6 +6,8 @@ import random
 import hopsworks
 import joblib
 import pandas as pd
+from sklearn.preprocessing import OneHotEncoder, LabelEncoder, StandardScaler
+
 
 
 project = hopsworks.login()
@@ -18,8 +20,6 @@ model_dir = model.download()
 model = joblib.load(model_dir + "/titanic_model_RF.pkl")
 
 def encode_features(df):
-  from sklearn.preprocessing import OneHotEncoder, LabelEncoder, StandardScaler
-  import pandas as pd
   non_numeric_features = ['embarked', 'sex', 'deck', 'title', 'family_size_grouped']
   for feature in non_numeric_features:
     df[feature] = LabelEncoder().fit_transform(df[feature])