Category: Business data analytics

1. Propose a business problem/scenario from any industry (e.g., retail, healthcare, banking, education) where:

A supervised learning algorithm (e.g., logistic regression, decision trees) can be used.

OR

An unsupervised learning algorithm (e.g., k-means clustering, hierarchical clustering) can be applied.

1. Data Understanding & Preprocessing
2. Briefly describe the dataset, including types of variables, number of observations, and sources.
3. Apply necessary data cleaning and preprocessing techniques (e.g., handling missing values, outliers, encoding, and normalization).
4. Justify the preprocessing steps taken.