| 000 | 02927cam a2200565Ki 4500 | ||
|---|---|---|---|
| 001 | 9781351204750 | ||
| 003 | FlBoTFG | ||
| 005 | 20220509193048.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 190805s2020 flu ob 001 0 eng d | ||
| 040 |
_aOCoLC-P _beng _erda _epn _cOCoLC-P |
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| 020 |
_a9781351204750 _q(electronic bk.) |
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| 020 |
_a1351204750 _q(electronic bk.) |
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| 020 |
_a9781351204736 _q(electronic bk. : EPUB) |
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| 020 |
_a1351204734 _q(electronic bk. : EPUB) |
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| 020 |
_a9781351204743 _q(electronic bk. : PDF) |
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| 020 |
_a1351204742 _q(electronic bk. : PDF) |
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| 020 |
_a9781351204729 _q(electronic bk. : Mobipocket) |
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| 020 |
_a1351204726 _q(electronic bk. : Mobipocket) |
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| 020 | _z9780815384205 | ||
| 020 | _z0815384203 | ||
| 020 | _z9780815384106 | ||
| 020 | _z0815384106 | ||
| 024 | 8 |
_a10.1201/9781351204750 _2doi |
|
| 035 | _a(OCoLC)1111577914 | ||
| 035 | _a(OCoLC-P)1111577914 | ||
| 050 | 4 |
_aQ325.5 _b.F38 2020eb |
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| 072 | 7 |
_aBUS _x061000 _2bisacsh |
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_aCOM _x000000 _2bisacsh |
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_aCOM _x012040 _2bisacsh |
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_aUY _2bicssc |
|
| 082 | 0 | 4 |
_a006.3/1 _223 |
| 100 | 1 |
_aFaul, A. C. _q(Anita C.), _eauthor. |
|
| 245 | 1 | 2 |
_aA concise introduction to machine learning / _cAnita Faul. |
| 264 | 1 |
_aBoca Raton, Florida : _bCRC Press, _c[2019] |
|
| 300 | _a1 online resource. | ||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 0 | _aChapman & Hall/CRC machine learning & pattern recognition | |
| 520 |
_a"Machine Learning is known by many different names, and is used in many areas of science. It is also used for a variety of applications, including spam filtering, optical character recognition, search engines, computer vision, NLP, advertising, fraud detection, robotics, data prediction, astronomy. Considering this, it can often be difficult to find a solution to a problem in the literature, simply because different words and phrases are used for the same concept. This class-tested textbook aims to alleviate this, using mathematics as the common language. It covers a variety of machine learning concepts from basic principles, and llustrates every concept using examples in MATLAB"-- _cProvided by publisher. |
||
| 505 | 0 | _aIntroduction -- Probability theory -- Sampling -- Linear classification -- Non-linear classification -- Dimensionality reduction -- Regression -- Feature learning. | |
| 588 | _aOCLC-licensed vendor bibliographic record. | ||
| 650 | 0 |
_aMachine learning _vTextbooks. |
|
| 650 | 7 |
_aBUSINESS & ECONOMICS / Statistics _2bisacsh |
|
| 650 | 7 |
_aCOMPUTERS / General _2bisacsh |
|
| 650 | 7 |
_aCOMPUTERS / Computer Graphics / Game Programming & Design _2bisacsh |
|
| 856 | 4 | 0 |
_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781351204750 |
| 856 | 4 | 2 |
_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
| 999 |
_c129124 _d129124 |
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