Normal Equation

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• An analytical way to find the best function

numpy.linalg.pinv(x.transpose * x) * x.transpose * y

• Gradient Descent vs. Normal Equation
• The latter migh work faster but only if the number of features is small. n = 10,000 might be the limit, depending on the computer power.

• Noninvertibility
• Redundant features: If two features are linearly dependent then the matrix is noninvertable (e.g. area in square mater and square feet)
• Too many features (m <= n) - delete some features or use regularization