SYMBOL INDEX (58 symbols across 8 files)

FILE: clv_automl/clv_automl.py
  function create_automl_model (line 35) | def create_automl_model(client,
  function deploy_model (line 130) | def deploy_model(client, model_name):
  function get_model_evaluation (line 143) | def get_model_evaluation(client, model_name):
  function do_batch_prediction (line 154) | def do_batch_prediction(prediction_client,
  function create_parser (line 186) | def create_parser():
  function main (line 241) | def main(argv=None):

FILE: clv_mle/trainer/btyd.py
  function load_data (line 37) | def load_data(datapath):
  function bgnbd_model (line 75) | def bgnbd_model(summary):
  function paretonbd_model (line 88) | def paretonbd_model(summary):
  function run_btyd (line 102) | def run_btyd(model_type, data_src, threshold_date, predict_end):
  function predict_value (line 159) | def predict_value(summary, actual_df, fitter, ggf, time_days, time_months):

FILE: clv_mle/trainer/context.py
  class CLVFeatures (line 20) | class CLVFeatures(object):
    method __init__ (line 64) | def __init__(self, ignore_crosses=False, is_dnn=None):
    method _keep_used (line 87) | def _keep_used(self):
    method get_key (line 105) | def get_key(self):
    method get_used_headers (line 108) | def get_used_headers(self, with_key=False, with_target=False):
    method get_defaults (line 129) | def get_defaults(self, headers_names=None, with_key=False):
    method get_all_names (line 146) | def get_all_names(self):
    method get_all_defaults (line 149) | def get_all_defaults(self):
    method get_unused (line 152) | def get_unused(self):
    method get_target_name (line 155) | def get_target_name(self):
    method _make_base_features (line 168) | def _make_base_features(self):
    method get_base_features (line 188) | def get_base_features(self):
    method _prepare_for_crossing (line 192) | def _prepare_for_crossing(self, key_name, num_bck, boundaries):
    method _make_crossed (line 223) | def _make_crossed(self):
    method get_wide_features (line 248) | def get_wide_features(self):
    method get_deep_features (line 264) | def get_deep_features(self, with_continuous=True):

FILE: clv_mle/trainer/model.py
  function parse_csv (line 41) | def parse_csv(csv_row):
  function dataset_input_fn (line 66) | def dataset_input_fn(data_folder, prefix=None, mode=None, params=None, c...
  function read_train (line 105) | def read_train(data_folder, params):
  function read_eval (line 114) | def read_eval(data_folder, params):
  function read_test (line 121) | def read_test(data_folder, params):
  function dnn_model (line 131) | def dnn_model(features, mode, params):
  function model_fn (line 162) | def model_fn(features, labels, mode, params):
  function rmse_evaluator (line 221) | def rmse_evaluator(labels, predictions):
  function get_learning_rate (line 234) | def get_learning_rate(params):
  function get_optimizer (line 258) | def get_optimizer(params):
  function get_estimator (line 288) | def get_estimator(estimator_name, config, params, model_dir):

FILE: clv_mle/trainer/task.py
  function create_parser (line 63) | def create_parser():
  function csv_serving_input_fn (line 160) | def csv_serving_input_fn():
  function main (line 187) | def main(argv=None):

FILE: run/airflow/dags/01_build_train_deploy.py
  function _get_project_id (line 34) | def _get_project_id():
  function get_model_type (line 130) | def get_model_type(**kwargs):
  function do_train_automl (line 143) | def do_train_automl(**kwargs):
  function do_train_ml_engine (line 249) | def do_train_ml_engine(**kwargs):
  function do_copy_model_to_final (line 273) | def do_copy_model_to_final(**kwargs):
  function do_check_model (line 320) | def do_check_model(**kwargs):
  function do_create_model (line 332) | def do_create_model(**kwargs):
  function do_list_versions (line 361) | def do_list_versions(**kwargs):
  function do_create_version (line 371) | def do_create_version(**kwargs):

FILE: run/airflow/dags/02_predict_serve.py
  function _get_project_id (line 32) | def _get_project_id():
  function get_model_type (line 71) | def get_model_type(**kwargs):
  function do_predict_mle (line 82) | def do_predict_mle(**kwargs):
  function do_predict_automl (line 111) | def do_predict_automl(**kwargs):
  function do_load_to_datastore (line 142) | def do_load_to_datastore(**kwargs):
  function do_list_predictions_files (line 174) | def do_list_predictions_files(**kwargs):
  function do_load_to_bq (line 199) | def do_load_to_bq(**kwargs):

FILE: run/airflow/gcs_datastore_transform.js
  function from_prediction_output_to_datastore_object (line 16) | function from_prediction_output_to_datastore_object(prediction_row, enti...