数学の苦手なバイオの学生がCourseraの機械学習コースを修了して気づいたこと ref: http://qiita.com/katsu1110/items/423fc9ac567710a1bd9b

file0.mat

% Compute covariance matrix
sigma = (X'*X)/size(X,1);
% Singular value decomposition
[U,S,V] = svd(sigma);

file0.txt

% Compute covariance matrix
sigma = (X'*X)/size(X,1);
% Singular value decomposition
[U,S,V] = svd(sigma);

file1.txt

J(\theta) = \frac{1}{2m} (X\theta - y)^{\mathrm{T}}(X\theta - y)

file2.mat

J = 0;
for i = 1:m
    for k = 1:n
        J = J + (X(i,k)*theta(k) - y(i))^2;
    end
end
J = J/(2*m);

file2.txt

J = 0;
for i = 1:m
    for k = 1:n
        J = J + (X(i,k)*theta(k) - y(i))^2;
    end
end
J = J/(2*m);

file3.mat

J = ((X*theta - y)'*(X*theta - y))/(2*m);

file3.txt

J = ((X*theta - y)'*(X*theta - y))/(2*m);