Used a regression model to accurately predict the price of the house based on the features. The provided dataset has 79 features.
Data exploration techniques, such as scatter plots, heat maps, box plots, histograms, and correlation analysis are used to gain insights into the relationships between features and the target variable.
Through exploratory data analysis, redundant features are identified that could be dropped as they had negligible impact on the house price prediction and could have negatively impacted the performance of the model, handled missing values, and encoded categorical variables to prepare the data for modeling. Subsequently, I trained a regression model on the preprocessed data to predict house prices.
Trained a regression model to predict the house price