本资源包含Pattern Recognition And Machine Learning的英文版和由马春鹏翻译的中文版。

面向模式的软件架构，卷1，英文版

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模式识别 Pattern Recognition 英文版 第四版 By Sergios Theodoridis

Information Science and Statistics 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 propagation. Similarly, new models based on kernels have had significant impact on both algorithms and applications.

The first version of this book was a set of lecture notes for a graduate course on data mining and applications in science and technology organized by the Swedish National Graduate School in Scientific Computing (NGSSC). Since then the material has been used and further developed for an undergraduate course on numerical algorithms for data mining and IT at Link¨oping University. This is a second course in scientific computing for computer science students.

压缩包中包含Pattern Recognition Letters的LateX模板和word模板。

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设计模式[Design_Pattern]可复用面向对象软件的基础.pdf