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020 _a9789352134571
035 _a(OCoLC)ocn895728667
040 _aBTCTA
_beng
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042 _alccopycat
082 0 4 _a005.133 MUL
100 1 _aMüller, Andreas C.,
_eauthor.
245 1 0 _aIntroduction to machine learning with Python :
_ba guide for data scientists /
_cAndreas C. Müller and Sarah Guido.
264 1 _aSebastopol, CA : Mumbai
_bO'Reilly Media, Inc., SPD
_c2017
300 _axii, 378 pages :
_billustrations ;
_c23 cm
500 _aRs.1200/- TB2196 Includes 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 _aPython (Computer program language)
650 0 _aProgramming languages (Electronic computers)
650 0 _aData mining.
650 7 _aData mining.
_2fast
_0(OCoLC)fst00887946
650 7 _aProgramming languages (Electronic computers)
_2fast
_0(OCoLC)fst01078704
650 7 _aPython (Computer program language)
_2fast
_0(OCoLC)fst01084736
650 7 _aMaschinelles Lernen
_2gnd
700 1 _aGuido, Sarah,
_eauthor.
906 _a7
_bcbc
_ccopycat
_d2
_encip
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_gy-gencatlg
942 _2ddc
_cBK