Implement Linear regression + gradient descent in python from scratch | univariate linear regression

In this video, you will learn how to implement linear regression and apply gradient descent from scratch using numpy in python.

you will also see how we can avoid for loops using vectorization to compute our hypothesis and calculate the required gradients/ partial derivatives to update the learnable parameters/ coefficients.

from the below notebook, hypothesis and gradient functions can be used for linear regression with multiple variables as well.

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[shajiaikram]

to calculate gradient, there are different formulas for both parameters. in the code above u have given same gradient value to both slope and intercept value