Burges discusses several useful techniques from applied mathematics frequently used in machine learning (and related fields, e.g. computer vision). While some sections may be used to refresh existing knowledge, others offer new perspectives on familiar material. Covered material includes lagrange multipliers, Singular Value Decomposition (SVD) as well as plenty of useful matrix properties.
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