The Maths Behind Linear Regression

Let us discuss Linear Regression, a type of Supervised Learning algorithm often used in Data Science and other ML related predictive models, and the maths behind it. Feature data values are also called independent variables because they are not influenced by anything, they are just the property of that particular dataset. Similarly target data values are also called dependent variables because they are in some way related to the feature or dependent variables. We know that our data will not all be related in the same linear manner. Based on this, our task in Linear Regression is to find the best possible relationship for which the error or deviation of the actual target from the target that we get from our relationship is as small as possible.