To find the optimal lambda for ridge regression, I defined a range of lambdavalues to test and created a ridge regression model and a grid search object.GridSearchCV finds an optimal parameter from a given set. I fitted the gridsearch object to the train set and calculated the cross-validation scores for eachvalue of lambda. The lambda value with the highest cross-validation score is theoptimal lambda so optimal lambda for ridge regression is found to be 1. So Itrained the ridge regression model with alpha=1 and got the regression score ofabout 0.27. The regression score for the OLS model was found to be about0.266. The ridge regression model only improved a little or barely improvedcompared to OLS