Using Pandas library load the time series dataset from the BB. Split the dataset into training set and test set. Use SD96 for training and 2D% for testing. Display the size of the train set and test set on the console. Plot the correlation matrix of dependent and independent variables using the seaborn package and heatmap function. Write down your observations about the correlation matrix. Collinearity detection: a. Perform SUD analysis on the original feature space and write down your observation ifco linearity exists. Justify your answer. b. Calculate the condition number and write down your observation if colinearity exists. Justify your answer. c. If eollinearity exist, how many features will you remove to avoid the eolinearity? Using Python, standardize the dataset and answer the following questions based on the standardized dataset