task, you are provided with two data files. The first one, MarketingCampaignsData.csv$,$ includes

information about:

Various demographic information about customers $-$ their age, job, marital status, and

education.

Customer account information $-$ more specifically, the status of their current credit $($default$),$

information about their past mortgage $($housing$)$ and$/$or personal loan applications $($loan$),$

and the preferred mode of contact $($mobile or landline$).$

Details about specific marketing campaign $-$ marketing campaign $($there were five in total,

$1-5),$ month and day of the week the customer was contacted, duration of the call $($in

seconds$),$ and the contact outcome $($success or failure, poutcome column$).$

The last column $($called y$)$ tells if the customer has eventually subscribed to a term deposit

$(\text{'}$yes$\text{'})$ or not $(\text{'}$no$\text{'}).$

Everything described above, with the exception of column y$,$ is contained in the second file,

ExistingCustomers.csv$,$ which contains data about the bank's present clients. Using the information

from the first file as a foundation, try to foresee which of the bank's present clients is most likely to

sign up for a term deposit. Determine who will subscribe, explain which criteria are most crucial

for forecasting client membership to a term deposit, and pick the optimal prediction technique

before creating a prediction model. Give a thorough justification of your analytical strategy,

including the workflow model's components. Describe the steps taken to obtain the most accurate

predictions. Give a thorough rundown of the results and expound on your conclusions.