Customer:

An American Real Estate Company wants to understand every aspect of the residential homes pricing market in Ames, Iowa, with a view of establishing an outlet in Iowa.

Problem:

I was contacted as a Data Scientist to understand the factors on which the pricing of houses depends. Specifically, they want to understand the factors affecting the pricing of homes, with a view of creating a web application that will be able to predict the price of house given its features.

The company wants to know:
● Which variables are significant in predicting the price of a house.
● How well do those variables describe the price of a house.

Solution:

I explore the Dataset and came up with insights that will aid the management to understand how exactly the prices vary with the independent variables.

With the insights, they can accordingly fit their business strategy to meet certain price levels. Also, this Exploration will be a good way for management to understand the pricing dynamics of the housing and estate market

Below is the python notebook that shows the EDA and machine learning models: