Compete in the House Prices: Advanced Regression TechniquesLinks to an external site. competition, where you will predict house prices in Ames, Iowa $($SalePrice$).$ You will be required to submit predictions to Kaggle.com and provide evidence of those submissions. As part of the analysis, you must address the following at a minimum.

Management$/$Research Question

In layman$$s terms, what is the management$/$research question of interest, and why would anyone care?

Requirements

Conduct your analysis using a cross$-$validation design.

Conduct EDA and provide appropriate visualizations in the process.

Build a minimum of two separate regression models using the training set.

Evaluate polynomial, indicator, dichotomous, & piecewise model components.

Create at least one feature from the data set.

Evaluate the models$$ assumptions.

Evaluate goodness of fit metrics on the training and validation sets.

Submit predictions for the unseen test set available on Kaggle.com.

Provide your Kaggle user name and a screen snapshot of your Kaggle scores.

Discuss what your models tell you in layman$$s terms

Python Programming

All programming will be done in Python.