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Fundamentals of Pattern Recognition and Machine Learning,312OfFSzxfL._AC_UF1000,,Pattern Recognition and Machine Learning (Information,Pattern Recognition and Machine Learning 1st Edition,61gDFPbfpqL.jpgPattern Recognition and Machine Learning (Information Science and Statistics) 2006年巻頭に8ページの黒ペンの書き込みありOPP袋に入れて、宅急便コンパクト専用梱包材に入れて、佐川急便/日本郵便での発送を予定しています。ROBERT FRANK 写真集　THE AMERICANS 1969年度版。\rコメントなしでの即購入歓迎。RY118 洋書古書 1969年北欧ヴィンテージ絵本 スウェーデン語絵本。Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation pro- gation. Similarly, new models based on kernels have had significant impact on both algorithms and applications.