Linear Regression in Machine learning
Mean Squared Error (MSE) is an evaluation metric that calculates the average of the squared differences between the actual and predicted values for all the data points. The difference is squared to ensure that negative and positive differences don’t cancel each other out. Utilizing the MSE function, the iterative process of gradient descent is applied […]
Linear Regression in Machine learning Read More »