Tag: house prices
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Python Data Science for Real Estate & REIT Amsterdam: (Auto) EDA, NLP, Maps & ML

The Amsterdam real estate market has experienced a significant resurgence, with property prices increasing by double digits annually since 2013. Data science is being used to analyze the city’s housing and rental markets, revealing insights on the impact of Airbnb and empowering communities with the necessary information. Comprehensive data analysis and machine learning techniques are…
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WA House Price Prediction: EDA-ML-HPO

A predictive model of house sale prices in King County, Washington, was developed using multiple supervised machine learning (ML) regression models, including LinearRegression, SGDRegressor, RandomForestRegressor, XGBRegressor, and AdaBoostRegressor. The best-performing model, XGBRegressor, explained 90.6% of the price variance, with a RMSE of $18472.7. These results, valuable to local realtors, indicate houses with a waterfront are…
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Supervised Machine Learning Use Case: Prediction of House Prices
This is the application of supervised machine learning to real estate. The goal is to predict sale prices ($) for N selected properties in a state (N>>1000). We are given a csv dataset as a NxM table, where M is the number of property features describing every aspect of the house and surroundings (typically, M<100). …