A data analytics project for exploring housing prices in King County, WA. Compare city and countryside properties with an interactive app and gain detailed insights into real estate market trends.

This project looks at the housing data for King County, Washington. I created a predictive model that accurately predicts houses within the lower 75% price bracket to an accuracy of 92%.

This repository includes my House Prices Multi-Variate Linear Regression-Flatiron School Module 2 Project. In this project I made use of the OSEMN methodology incorporating packages such as Pandas, NumPy, Matplotlib, Seaborn, and Scikit-Learn.

Best place to live in King County

This repository contains a linear regression model to predict the price of a home in King County, Washington.

This repository contains simple usage examples for basic machine learning libraries. These notebooks are tested in Colab.

Predicting house prices using different regression analysis models.

Linear Regression predicting King County Housing Data Modeling

Developing a Regression Model to Predict Housing Prices in King County in Washington

This repository contains a price prediction model for King County, Washington. The model results and analysis would prove invaluable to investors and stakeholders in the King County, WA housing market.

Multiple Regression on House Data

CatBoost achieves $50,860 MAE (89.25% accurate) on King County house prices. 8 preprocessing versions | 7 models | Full ablation study | Production-ready. From raw chaos to 10.75% error — preprocessing is 80% of ML.