This is my code for a competition I participated in (3rd programming competition Bahrain AI) using Kaggle

Which is a model to predict the sales price of a house from given variables.

Input file: house_data_test4.csv

Output file: will be generated after running the code as submission.csv

The variables in the input file: • id: It represents the identification number or unique identifier of each property.
• bedrooms: It represents the number of bedrooms in the property.
• bathrooms: It represents the number of bathrooms on the property.
• metersq_living: It represents the total living area in square meters.
• metersq_lot: It represents the total lot area in square meters.
• floors: It represents the number of floors in the property.
• waterfront: It is a binary variable indicating whether the property has a waterfront view or not (1 for waterfront, 0 for no waterfront).
• view: It represents the level of view the property has.
• condition: It represents the overall condition of the property.
• grade: It represents the overall grade given to the property.
• metersq_above: It represents the living area above ground level in square meters.
• metersq_basement: It represents the living area in the basement in square meters.
• yr_built: It represents the year the property was built.
• block_no: It represents the block number or identifier of the property.
• location1: It represents the first-level location information of the property.
• location2: It represents the second-level location information of the property.
• metersq_built: It represents the total built area in square meters.
• metersq_land: It represents the total land area in square meters.