2017, ISBN: 9780387310732

[ED: Buch], [PU: Springer Nature Singapore], Neuware - Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities… Mehr…

[ED: Buch], [PU: Springer Nature Singapore], Neuware - 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. This new textbook reacts these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as wellas researchers and practitioners, and assumes no previous knowledge of pattern recognition or - chine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory., DE, [SC: 0.00], Neuware, gewerbliches Angebot, 260x185x40 mm, 778, [GW: 1482g], Banküberweisung, PayPal, Offene Rechnung (Vorkasse vorbehalten)<

2006, ISBN: 9780387310732

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 tog… Mehr…

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. This new textbook reacts these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as wellas researchers and practitioners, and assumes no previous knowledge of pattern recognition or - chine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory. Books Christopher M. Bishop|Hardback|Springer-Verlag New York Inc.|17/08/2006, Springer-Verlag New York Inc.<

ISBN: 9780387310732

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 tog… Mehr…

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. This new textbook reacts these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as wellas researchers and practitioners, and assumes no previous knowledge of pattern recognition or - chine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory. Fremdsprachige Bücher 18.5 x 26.0 x 4.0 cm , Springer Us, Springer Us<

2006, ISBN: 9780387310732

Springer, Hardcover, Auflage: Newer (Colored), 798 Seiten, Publiziert: 2006-08-17T00:00:01Z, Produktgruppe: Book, Hersteller-Nr.: 0387310738SRQ, 1.05 kg, Verkaufsrang: 74103, AI & Machine… Mehr…

Springer, Hardcover, Auflage: Newer (Colored), 798 Seiten, Publiziert: 2006-08-17T00:00:01Z, Produktgruppe: Book, Hersteller-Nr.: 0387310738SRQ, 1.05 kg, Verkaufsrang: 74103, AI & Machine Learning, Computer Science, Computing & Internet, Subjects, Books, Amazon, Online Shopping, Digital Lifestyle, Algorithms, Programming, Graphics & Multimedia, Software Design, Testing & Engineering, Higher Education, Education, Engineering & Technology, Science, Nature & Maths, Engineering Physics, Mathematics, Probability & Statistics, Statistics & Probability, Applied Mathematics, Scientific, Technical & Medical, School Books : Promotion, 3e708b60-20fb-41e8-a18d-05c77fb89b4c_6001, 3e708b60-20fb-41e8-a18d-05c77fb89b4c_0, Arborist Merchandising Root, Great Deals in Books for Study, 579c3025-5e5c-446b-80c9-b24e6fd5c94f_3601, 579c3025-5e5c-446b-80c9-b24e6fd5c94f_0, Special Features Stores, Books Global Store, Format: Illustrated, Springer, 2006<