Machine Learning Regression - Seattle House Price Prediction

Description

• In this project, we developed and evaluated different linear regression models for predicting house sale price in Seattle King County.
• We implemented ridge, lasso, gradient descent techniques for modeling optimization.

Code

1. Simple Linear Regression
2. Multiple Linear Regression
3. Multiple Linear Regression with Gradient Descent Optimization
4. Polynomial Regression
5. Ridge Regression
6. Ridge Regression with Gradient Descent Optimization
7. Lasso Regression
8. Lasso Regression Coordinate Descent
9. Nearest Neighbor Regression

Data

The data for these sales comes from the official public records of home sales in the King County area, Washington State. The data sets contains 19 house features plus the price and the id, along with 21613 observations. Each represents a home sold from May 2014 through May 2015. More detailed explanation of each variable could be found here, at Kaggle website.