Development ML model to predict US Real Estate housing prices

Observing the current market volatility, interest rates hikes, risks of recession in 2023 and 2024; it is highly important to have tools that provide more confindence to families at the moment comminting to large investments such as buying a poroperty. The scope for this project is limited to the US and various cities are analized as well as US at a country level.

The goal of this project is to provide a data driven solution to families looking to by a single-family property to minimize risks and increase confidence in real estate investments while acquiring the best deals and being able to afford the family's dream home.

Factors that are taken in consideration are:

1. Interest Rates
2. Country GDP
3. Employment Ratio
4. Working Age Population
5. Population Level
6. Dates ( from 200 to 2023)
7. Type of property ( condo/coops ($), or homes with 1, 2, 3, 4 and 5+ bedrooms)

1. 523 columns containing typical value for all single-family homes in the respective cities monthly for condo/coops ($), and homes with 1, 2, 3, 4 and 5+ bedrooms
2. 1 columns con containing typical value for all single-family homes in the United States monthly for condo/coops ($), and homes with 1, 2, 3, 4 and 5+ bedrooms
3. Data Source: Contains if the row value corresponds to condo/coops ($), or homes with 1, 2, 3, 4 and 5+ bedrooms
4. Date: Contains date, by month
5. Interest Rate: It is the interest rate for the respective month [%] in US
6. Pop_Level: Count the population level in US in thousands of Persons
7. Working Age Population: Count of working age population in the US
8. Employment Ratio: Percentage of employment in the US
9. GDP: Quarterly measurement of Gross Domestic Product in the US