Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. In its simplest form, simple linear regression examines how a single predictor variable relates to an outcome by fitting a straight line through the data. The line is chosen so that the sum of the squared differences, known as residuals, between the observed data points and the predicted values is minimized. This process, called the least squares method, pr
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AI • Machine Learning • Tech on Instagram: "Linear regression is a curve-fitting technique that models a linear relationship between variables by adjusting 2 parameters to move the line. In its simplest 2D form, the model is written as y=mx+b, where the slope m controls the tilt of the line and the intercept b shifts the line up or down. Learning these parameters corresponds to finding the line that best fits the data in a least-squares sense. This idea generalizes naturally to higher dimensions
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