In this project, we will explore the application of unsupervised learning techniques to analyze and understand airline passenger satisfaction.

The dataset we will be working with contains information about individuals, including their age, education, occupation, marital status, and more. We have a total of 32,561 observations and 15 variables, including the target variable "income," which indicates whether an individual's income is less than or equal to $50,000 per year or more.

In this scenario, we want to know what factors influence the worldwide `selling price of laptops`, and we want to know: - Which variables are important in forecasting `laptop pricing` - how effectively the variable describes a `laptop's price`

Access to clean drinking water is critical to health, a basic human right, and a component of any health-protection strategy. This is significant as a national, regional, and local health and development concern. It has been demonstrated in some locations that investments in water supply and sanitation can result in a net economic gain since the reductions in adverse health impacts and health care expenditures surpass the price of carrying out the interventions.

This dataset contains information on international shipments of a port. The dataset includes the name of the product, its price, weight, length, width, and height, as well as the date it was shipped and the destination port. This data set take time in 2023 March.