Machine Learning, Probability, Statistics, Data Science, Deep Learning.
error: It is the average of difference between the original and predicted values. Mean squared error: it is the average of square of difference between the original and predicted values. from sklearn.metrics import mean_squared_error y_true = [3, -0.5, 2, 7] y_pred = [2.5, 0.0, 2, 8]