Bank Marketing Model Training and Prediction | Sample Use Cases | Open Analytics Framework on VantageCloud Lake - Bank Marketing Model Training and Prediction

Use case: Build a model that can accurately predict term deposit subscriptions from a customer.

The model includes the following parameters:

age: Age of customer.
job: Job of customer.
marital: marital status.
education: education background.
default_value: whether customer is default or not.
balance: current balance.
housing: housing status.
loan: Whether customer is having loan or not.
contact: contact type.
day_of_month: day of month for contacting.
month_of_year: month of year for contacting.
duration: duration.
campaign: campaign.
pdays: pdays.
previous: previous customer or not.
poutcome: previous outcome.

This model also includes the following target variable:

deposit: Whether customer will opt for term deposit subscriptions or not.

Prerequisite steps:

Connect from a client to a target VantageCloud Lake system where the scoring task will be performed.

Load the python libraries.

import getpass
import json
import tempfile
from teradataml import create_context, create_env, DataFrame, display, get_env, load_example_data, OrderedDict, remove_context, remove_env, set_auth_token, TrainTestSplit, view_log, set_user_env
from teradatasqlalchemy import BLOB, CLOB, FLOAT, INTEGER, TIMESTAMP, VARCHAR

ues_url = input("UES URL: ")
set_auth_token(ues_url=ues_url)

Bank Marketing Model Training and Prediction | Sample Use Cases | Open Analytics Framework on VantageCloud Lake - Bank Marketing Model Training and Prediction - Teradata Vantage

Teradata® VantageCloud Lake