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Zeezahbeautyplanet/Nigeria-House-Price-Prediction-

Domain:

socioeconomic

Record type:

project
Creator:
Zee
Host:
This project focuses on predicting house prices in Nigeria based on key features such as location, number of rooms, house type, and more. The goal is to build a machine learning model that can accurately forecast house prices, providing valuable insights for potential buyers, real estate developers, and investors. # Nigeria-House-Price-Prediction- This project focuses on predicting house prices in Nigeria based on key features such as location, number of rooms, house type, and more. The goal is to build a machine learning model that can accurately forecast house prices, providing valuable insights for potential buyers, real estate developers, and investors. Key highlights: Data Processing: Cleaned and prepared data for modeling. Feature Engineering: Created meaningful features from raw data to improve model performance. Modeling: Applied regression models (Linear Regression, Decision Trees, etc.) to predict house prices. Visualization: Developed an interactive Streamlit web app to showcase house price trends and predictions. Dashboard: Created a Power BI dashboard for dynamic visualization of house price distribution across regions. This project demonstrates the power of data in solving real-world problems in the real estate sector.

Visit

github.com

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