Problem Statement
Finding the correct property to live in is a crucial task while moving to a new city/location. An inappropriate property can make our life miserable. Can AI help us find better places?
Task
You have given a relevant dataset about various properties in the USA. Your task is to identify the habitability score of the property.
The columns provided in the dataset are as follows:
DATA Description
Property_ID : Represents a unique identification of a property
Property_Type : Represents the type of the property( Apartment, Bungalow, etc)
Property_Area : Represents the area of the property in square feets
Number_of_Windows : Represents the number of windows available in the property
Number_of_Doors : Represents the number of doors available in the property
Furnishing : Represents the furnishing type ( Fully Furnished, Semi Furnished, or Unfurnished )
Frequency_of_Powercuts : Represents the average number of power cuts per week
Power_Backup : Represents the availability of power backup
Water_Supply : Represents the availability of water supply ( All time, Once in a day - Morning, Once in a day - Evening, and Once in two days)
Traffic_Density_Score : Represents the density of traffic on a scale of 1 to 10
Crime_Rate : Represents the crime rate in the neighborhood ( Well below average, Slightly below average, Slightly above average, and Well above average )
Dust_and_Noise : Represents the quantity of dust and noise in the neighborhood ( High, Medium, Low )
Air_Quality_Index : Represents the Air Quality Index of the neighborhood
Neighborhood_Review : Represents the average ratings given to the neighborhood by the people
Habitability_score : Represents the habitability score of the property
