Problem statement

Let’s dive into a case study where we’ll explore the art of predicting house prices using historical data. Picture this: we have a treasure trove of valuable information about houses, including details such as zoning, lot area, building type, overall condition, year built, and sale price. Our goal is to harness the power of ML to accurately forecast the price of a new house that comes our way.

To accomplish this feat, we’ll embark on a journey to construct an ML model exclusively designed for predicting house prices. This model will leverage the existing historical data and incorporate additional features. By carefully analyzing and understanding the relationships between these features and the corresponding sale prices, our model will become a reliable tool for estimating the value of any new house that enters the market.

To achieve this, we will go through some of the steps defined in the previous section, where we talked about the ML...