The Bank Marketing Dataset is a well-known dataset from the UCI Machine Learning Repository. It is used for predicting whether a customer will subscribe to a term deposit based on various features. The dataset is related to a direct marketing campaign conducted by a Portuguese banking institution.

Key Information:

• Data Source: UCI Machine Learning Repository (often referred to as “UCI”).
• Features: The dataset contains both numerical and categorical features such as:
  • Age
  • Job type (e.g., admin, technician, etc.)
  • Marital status
  • Education level
  • Default status (whether the client has credit in default)
  • Balance
  • Housing loan status
  • Personal loan status
  • Contact communication type (e.g., cellular, telephone)
  • Last contact duration
  • Campaign-related features (e.g., number of contacts performed during the campaign)
  • Outcome of the previous campaign
  • Other demographic and campaign attributes.
• Target variable: The dataset’s target variable is whether the client subscribes to the term deposit (“yes” or “no”).

Usage:

It is typically used for classification tasks, where the goal is to predict whether a client will subscribe to a term deposit based on the given features.

You can find more details and the dataset itself on the UCI repository page.

https://www.kaggle.com/datasets/adityamhaske/bank-marketing-dataset