Gradient Descent in Linear Regression

This article was published as a part of the Data Science Blogathon. Introduction A linear regression model attempts to explain the relationship between a dependent (output variables) variable and one or more independent (predictor variable) variables using a straight line. This straight line is represented using the following formula: y = mx +c Where, y: … Continue reading Gradient Descent in Linear Regression

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