Project 1: Real Estate Price Predictor

  • Designed a model that estimates the prices of real estate (Median value of owner-occupied homes in $1000’s) to optimize future real estate purchases (minimizing losses) as housing prices are an important reflection of the economy, and housing price ranges are of great interest for both buyers and sellers.

  • Dataset - Scraped and fetched data from the UCI ML Repository for the model. The Dataset includes various features describing the housing situation in Boston such as Number of Rooms, Crime Rate, Tax ,etc.

  • Model - The major aim in this project is to predict the house prices based on the features using some of the regression techniques and algorithms. Optimized Linear, DecisionTree and Random Forest Regressors using GridsearchCV to reach the best model.

Scatter Graph giving us a vizualization of the actual prices vs the predicted prices

Vizaulization of the heatmap of correlation between the features

Please Check out my Github Repository for all the details: Link to Github Repository