A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.
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linear brought down but not as effective as random forest
c2bd1ccView on GitHubrandom forest reduces the root mean square error by 25 percent
35fe073View on GitHubremoving super expensive properties to have an even distribution
289f854View on GitHubsad lyf - cant print feature names post one hot encoding
caec748View on GitHubml model 0.0 - needs dropping first column after one hot encoding, analysis of coefficients, integrating economic and crime data of zip codes, and excluding more outliers by filtering out properties above 2 mil
1ee2a23View on GitHubfiltered outliers, now I can get started on modeling
19ec23aView on GitHub