000			01936cam a22002897i 4500
020			_a9781449369415
020			_a1449369413
082	0	4	_a005.133 _223 _bMUL
100	1		_aMüller, Andreas C.
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/O'Reilly, _c2017.
300			_axii, 376 pages : _billustrations ;
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. --
650		0	_aPython (Computer program language)
650		0	_aProgramming languages (Electronic computers)
650		0	_aData mining.
650		7	_aData mining.
650		7	_aProgramming languages (Electronic computers)
650		7	_aPython (Computer program language)
650		7	_aMaschinelles Lernen
700	1		_aGuido, Sarah,
942			_cBK
999			_c666189 _d666189