| Record ID | ia:patternrecogniti0000bish |
| Source | Internet Archive |
| Download MARC XML | https://archive.org/download/patternrecogniti0000bish/patternrecogniti0000bish_marc.xml |
| Download MARC binary | https://www.archive.org/download/patternrecogniti0000bish/patternrecogniti0000bish_meta.mrc |
LEADER: 02790cam 2200637Ia 4500
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035 $a(CSdNU)u353928-01national_inst
035 $a(OCoLC)71008143
035 $a(OCoLC)71008143
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050 00 $aQ327$b.B52 2006
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100 1 $aBishop, Christopher M.
245 10 $aPattern recognition and machine learning /$cChristopher M. Bishop.
260 $aNew York :$bSpringer,$cc2006.
300 $axx, 738 p. :$bill. (chiefly col.) ;$c25 cm.
440 0 $aInformation science and statistics
500 $aTextbook for graduates.
504 $aIncludes bibliographical references (p. 711-728) and index.
505 0 $a1. Introduction -- 2. Probability distributions -- 3. Linear models for regression -- 4. Linear models for classification -- 5. Neural networks -- 6. Kernel methods -- 7. Sparse kernel machines -- 8. Graphical models -- 9. Mixture models and EM -- 10. Approximate inference -- 11. Sampling methods -- 12. Continuous latent variables -- 13. Sequential data -- 14. Combining models.
650 0 $aPattern perception.
650 0 $aPattern recognition systems.
650 0 $aMachine learning.
650 6 $aReconnaissance des formes (Informatique)$vManuels d'enseignement superieur.
650 6 $aApprentissage automatique$vManuels d'enseignement superieur.
650 6 $aReconnaissance des formes (Informatique)$vProblemes et exercices.
650 6 $aApprentissage automatique$vProblemes et exercices.
650 6 $aStatistique mathematique.
650 17 $aPatroonherkenning.$2gtt
650 17 $aMachine-learning.$2gtt
650 7 $aRedes neurais.$2larpcal
650 7 $aReconhecimento de padroes.$2larpcal
650 7 $aAprendizado computacional.$2larpcal
938 $aOtto Harrassowitz$bHARR$nhar050151382
938 $aYBP Library Services$bYANK$n2375921
938 $aBaker and Taylor$bBTCP$nBK0006705640
938 $aBaker & Taylor$bBKTY$c84.95$d84.95$i0387310738$n0006705640$sactive
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