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  221222s2022 maua b 001 0 eng

• 010

  ▼a 2021027430

• 020

  ▼a  9780262046824
  ▼q  (hardcover) :
  ▼c  GBP96.00

• 035

  ▼a  (KERIS)BIB000016218991

• 040

  ▼a  211009
  ▼c  211009
  ▼d  211047

• 042

  ▼a  pcc

• 050

  ▼a  Q325.5
  ▼b  .M872 2022

• 082

  ▼a  006.3/1
  ▼2  23

• 090

  ▼a  006.31
  ▼b  M95p

• 100

  ▼a  Murphy, Kevin P.,
  ▼d  1970-,
  ▼e  author.

• 245

  ▼a  Probabilistic machine learning :
  ▼b  an introduction /
  ▼d  Kevin P. Murphy.

• 260

  ▼a  Cambridge, Massachusetts :
  ▼b  The MIT Press,
  ▼c  2022.

• 300

  ▼a  xxix, 826 p. :
  ▼b  ill. (some col.) ;
  ▼c  24 cm.

• 490

  ▼a  Adaptive computation and machine learning series

• 504

  ▼a  Includes bibliographical references and index.

• 520

  ▼a  "This book provides a detailed and up-to-date coverage of machine learning. It is unique in that it unifies approaches based on deep learning with approaches based on probabilistic modeling and inference. It provides mathematical background (e.g. linear algebra, optimization), basic topics (e.g., linear and logistic regression, deep neural networks), as well as more advanced topics (e.g., Gaussian processes). It provides a perfect introduction for people who want to understand cutting edge work in top machine learning conferences such as NeurIPS, ICML and ICLR"-- Provided by publisher.

• 650

  ▼a  Machine learning.

• 650

  ▼a  Probabilities.

• 830

  ▼a  Adaptive computation and machine learning series.

• 990

  ▼b  학술정보지원