A few key points…

Author(s): Lawrence Alaso Krukrubo

Originally published on Towards AI.

Using matrix algebra…

Hello World, ever wondered how your favourite Machine Learning algorithms actually work? Let’s see how a Multiple Linear Regression(MLR) model computes the ideal parameters, given the features matrix (X) and target variable(y), using Linear Algebra.

X is an (m * n feature matrix) and y is an(m* 1 column vector)

Where:

m is the number of observations or rows in the data set

n is the number of attributes or variables selected for the prediction

X is the m * n feature matrix of independent variables

y is the target or dependent variable

I assume you know the basics of linear regression and can walk through the… Read the full blog for free on Medium.

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Published via Towards AI