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020 _a9783110595567
024 7 _a10.1515/9783110595567
_2doi
035 _a(DE-B1597)494024
035 _a(OCoLC)1163878103
040 _aDE-B1597
_beng
_cDE-B1597
_erda
041 0 _aeng
044 _agw
_cDE
100 1 _aZhang, Baochang,
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_976902
245 1 0 _aMachine Learning and Visual Perception /
_cBaochang Zhang.
264 1 _aBerlin ;
_aBoston :
_bDe Gruyter,
_c[2020]
264 4 _c©2020
300 _a1 online resource (X, 142 p.)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 0 _aDe Gruyter Textbook
505 0 0 _tFrontmatter --
_tContents --
_tIntroduction --
_t1. Introduction of machine learning --
_t2. PAC Model --
_t3. Decision tree learning --
_t4. Bayesian learning --
_t5. Support vector machines --
_t6. AdaBoost --
_t7. Compressed sensing --
_t8. Subspace learning --
_t9. Deep learning and neural networks --
_t10. Reinforcement learning --
_tBibliography --
_tIndex
506 0 _arestricted access
_uhttp://purl.org/coar/access_right/c_16ec
_fonline access with authorization
_2star
520 _aThe book provides an up-to-date on machine learning and visual perception, including decision tree, Bayesian learning, support vector machine, AdaBoost, object detection, compressive sensing, deep learning, and reinforcement learning. Both classic and novel algorithms are introduced. With abundant practical examples, it is an essential reference to students, lecturers, professionals, and any interested lay readers.
530 _aIssued also in print.
538 _aMode of access: Internet via World Wide Web.
546 _aIn English.
588 0 _aDescription based on online resource; title from PDF title page (publisher's Web site, viewed 27. Jan 2023)
700 1 _aTsinghua University Press,
_econtributor.
_4ctb
_4https://id.loc.gov/vocabulary/relators/ctb
_975695
773 0 8 _iTitle is part of eBook package:
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856 4 0 _uhttps://doi.org/10.1515/9783110595567
856 4 0 _uhttps://www.degruyter.com/isbn/9783110595567
856 4 2 _3Cover
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