function [theta, J_history] = gradientDescentMulti(X, y, theta, alpha, num_iters)

m = length(y); % number of training examples

J_history = zeros(num_iters, 1);

for iter = 1:num_iters

    theta = theta - alpha * X' * (X * theta - y) / m;

    iter = iter +1;

   J_history(iter) = computeCostMulti(X, y, theta);

end

end

　　

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