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082 0 4 _a005.133
_223
_bM9581i
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.
246 3 0 _aMachine learning with Python
250 _aFirst edition.
260 _aMumbai:
_bShroff Publishers and Distributors Pvt.Ltd.,
_c2017
300 _axii, 376 pages :
_billustrations ;
_c24 cm
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. --
526 _aCSE
_bps
_lREF
541 _aRisaam
650 0 _aPython (Computer program language)
650 0 _aProgramming languages (Electronic computers)
650 0 _aData mining.
650 7 _aData mining.
_2fast
650 7 _aProgramming languages (Electronic computers)
_2fast
650 7 _aPython (Computer program language)
_2fast
650 7 _aMaschinelles Lernen
_2gnd
700 1 _aGuido, Sarah,
_eauthor.
942 _2ddc
_cBK
999 _c57746
_d57920