Kaggle competition: Home Credit Default Risk
TRAIN_PATH = ".. /input/dogs-vs-cats-redux-kernels-edition/train.zip"
TEST_PATH = ".. /input/dogs-vs-cats-redux-kernels-edition/test.zip"
UNZIP_DATA = ".. /kaggle/files/unzipped/"
UNZIP_TRAIN = ".. /kaggle/files/unzipped/train"
UNZIP_TEST = ".. /kaggle/files/unzipped/test"
BATCH_SIZE = 32
SEED = 88888
IMG_SIZE = 224
EPOCHS = 10 
<load_pretrained>
avg_bleand_1 = pd.DataFrame()
avg_bleand_1['SK_ID_CURR'] = df_subs['SK_ID_CURR']
avg_bleand_1['TARGET'] = 1.0 *(6 *(df_subs['0'] + df_subs['1'] + df_subs['2'] + df_subs['3'] + 2 * df_subs['4'])/ 6 +
3 *(5 * df_subs['5'] + 7 * df_subs['6'] + 1 * df_subs['14'] + 3 * df_subs['19'] + 2 * df_subs['20'] + 4 * df_subs['21'])/ 22 +
25 *(df_subs['7'] + df_subs['8'] + df_subs['9'] + df_subs['10'] + df_subs['11'] + df_subs['12'] + 2 *
df_subs['13'] + 4 * df_subs['15'] + 2 * df_subs['16'] + 2 * df_subs['17'] + 4 * df_subs['18'])/ 20)/ 34
avg_bleand_1.head()
with zipfile.ZipFile(TRAIN_PATH, 'r')as zipp:
zipp.extractall(UNZIP_DATA)
 print('Done!')
 with zipfile.ZipFile(TEST_PATH, 'r')as zipp:
zipp.extractall(UNZIP_DATA)
 print('Done!' )<define_variables>
avg_bleand_1.to_csv('submission_806.csv', index=False )
training_images_files = os.listdir(".. /kaggle/files/unzipped/train")
 test_image_files =os.listdir(".. /kaggle/files/unzipped/test")
<feature_engineering>
df_subs['25'] = avg_bleand_1['TARGET']
<feature_engineering><EOS> 
avg_bleand_2 = avg_bleand_1.copy()
avg_bleand_2['TARGET'] = 1.0*(7*df_subs['22'] + 12*df_subs['23'] + 16*df_subs['24'] - 5*df_subs['25'])/ 31
avg_bleand_2.to_csv('submission_final.csv', index=False )