You have just joined a new "full stack" real estate company in Ames, Iowa. The strategy of the firm is two-fold:

• Own the entire process from the purchase of the land all the way to sale of the house, and anything in between.
• Use statistical analysis to optimize investment and maximize return. The company is still small, and though investment is substantial the short-term goals of the company are more oriented towards purchasing existing houses and flipping them as opposed to constructing entirely new houses. That being said, the company has access to a large construction workforce operating at rock-bottom prices.

Develop an algorithm to reliably estimate the value of residential houses based on fixed characteristics.

Identify characteristics of houses that the company can cost-effectively change/renovate with their construction team.

Evaluate the mean dollar value of different renovations.

• Cleaning and Feature-Engineering of data
• Identify fixed vs changeable features
• For the 3rd step, my first use of SMOTE to address class imbalance.

• Linear Regression used to regress vs fixed characteristics, with Regularizaion to effectively remove unimportant features and colinearity
• Isolate residuals and model those separately as being influence by changeable features

• Evaluate coefficients for reasonableness
• Train a model on pre-2010 data and evaluate its performance on the 2010 houses.