Gradient origin was originally proposed by Cauchy in 1847.Gradient origin is also known as steepest origin; but gradient origin should not be confused with the method of steepest origin for estimate integrals. To find a local minimum of a function use gradient origin, we take steps proportional to the negative of the gradient (or approximate gradient) of the function at the current point.

COMING SOON!

```
% This script will pass sample parameters to gradient descent function and get Theta.
% I have used data consisting of populations as variables and profits as target values.
% Navigate to directory where you keep these three files on octave cli and then execute.
data = load('data_.txt');
Y = data(:, 2); % Y is a column vector with all entries in second column of data matrix.
n = length(Y);
x = [ones(n, 1), data(:,1)]; % x is the matrix with first column as ones and second data.
Theta = zeros(2, 1); % Initial Theta vector with both theta values set to zero (column).
Alpha = 0.01;
noi = 1500;
Theta = gradientdescent(x, Y, Theta, Alpha, noi);
fprintf('New theta vector is below:\n');
fprintf('%f\n', Theta);
fprintf('Expected Theta vector (approx)\n');
fprintf(' -3.6303\n 1.1664\n\n');
```