Matlab, Gradient Descent, Linear Regression, Octave, Machine Learning.
gradient descent gets to the lowest cost. function j = cost(thetas, xo, y) hc = xo * thetas — y; m = length(y); j = (hc’ * hc) / (2 * m); end Step 5: Predict our result Finally, back in our main program, lets: Plot our cost so we can get a visual queue on the costs. Get a matrix of the features