Linear Regression to calculate Price of a Lego set

The workflow trains a Linear Regression model to predict the price of a Lego set based on it's various features. It includes the process of:
- Loading the Lego dataset and cleaning it to remove missing values and outliers
- Remove collinearity between independent variables
- Partitioning the dataset into train and test dataset
- Modelling a Linear Regressor and prediciting sales of lego sets in test data
- Calculate the accuracy metrics of the model
- Plot residual plot and histogram to visualize Linear Regression assumptions of homoscedasticity (constant variance) and normal distribution of error.