mratsim/Apartment-Interest-Prediction

Predict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.

19
/ 100
Experimental

This project helps real estate professionals and rental agencies predict how interested potential renters will be in specific New York City apartments. It takes in structured apartment data (like price, number of rooms), location details, text descriptions, and even some image metadata, then outputs a prediction of whether an apartment will generate low, medium, or high interest from prospective tenants. It's designed for anyone managing apartment listings who wants to prioritize marketing efforts or understand rental demand.

No commits in the last 6 months.

Use this if you need to quickly assess the potential demand for new apartment listings in NYC based on various apartment attributes and historical data.

Not ideal if you're looking for a simple, out-of-the-box application with a user interface, as this project is a code-based solution requiring technical expertise to implement.

real-estate rental-market demand-forecasting NYC-apartments property-management
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 5 / 25

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Jupyter Notebook

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Last pushed

Nov 04, 2017

Commits (30d)

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