Calculate the hypothesis h = X * theta.Calculate the loss = h – y and maybe the squared cost (loss^2)/2m.Calculate the gradient = X’ * loss / m.Update the parameters theta = theta – alpha * gradient.

How do you find the gradient of a gradient descent in Python?

1. Calculate the hypothesis h = X * theta.
2. Calculate the loss = h – y and maybe the squared cost (loss^2)/2m.
3. Calculate the gradient = X’ * loss / m.
4. Update the parameters theta = theta – alpha * gradient.

How do you find the gradient descent of a function?

1. Compute the gradient (slope), the first order derivative of the function at that point.
2. Make a step (move) in the direction opposite to the gradient, opposite direction of slope increase from the current point by alpha times the gradient at that point.