Numpy Pandas
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Linear Regression is a machine learning algorithm.
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It attempts to model the relationship between TWO variables by fitting a ”best-fit” line to the observed data points where the ”best-fit” line has the minimum sum of the squares of the vertical distance from each data point to the ”best-fit” line.
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The method of minimizing the sum of the squares of the vertical distance from each data point to the line is known as the method of least-squares.
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The variables in Linear Regression is known as dependent variable and independent variable. The idea is to derive the independent variable using the dependent variable.
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In Multiple Linear Regression, there are more than one dependent variable and exactly one independent variable.