000 02696cam a2200457 i 4500
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008 170710s2017 cc a 001 0 eng d
010 _a 2017394288
020 _a9781449369415
_qpaperback
035 _a(OCoLC)ocn895728667
040 _aBTCTA
_beng
_cBTCTA
_erda
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042 _alccopycat
050 0 0 _aQA76.73.P98
_bM85 2016
082 0 4 _a005.133 MU.I 2016
_223
100 1 _aMüller, Andreas C.,
_eauthor.
245 1 0 _aIntroduction to machine learning with Python :
_ba guide for data scientists /
_cAndreas C. Müller, Sarah Guido.
246 3 0 _aMachine learning with Python
250 _aFirst edition.
264 1 _aBeijing :
_bO'Reilly Media, Inc.,
_c2016.
300 _axii, 384 pages :
_billustrations ;
_c24 cm.
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
500 _aIncludes index.
505 0 _aIntroduction -- Supervised learning -- Unsupervised learning and preprocessing -- Representing data and engineering features -- Model evaluation and improvement -- Algorithm chains and pipelines -- Working with text data -- Wrapping up.
520 _aMachine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. --
_cProvided by publisher.
650 0 _aMachine learning.
650 0 _aPython (Computer program language)
650 0 _aData mining.
700 1 _aGuido, Sarah,
_eauthor.
856 4 1 _uhttps://ebookcentral.proquest.com/lib/coventry/detail.action?docID=4698164&query=Introduction+to+machine+learning+with+Python
906 _a7
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998 _amona.romia
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999 _c318
_d318