000			02043cam a22003017i 4500
005			20240116114422.0
008			100220t20162017caua 001 0 eng d
020			_a9781449369415
040			_aUISEK-EC _bspa _erda
082	0	4	_a005.133 _bM685in 2017
100	1		_aMüller, Andreas C., _95320 _eaut
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			_aPrimera edición
264		1	_aSebastopol, CA : _bO'Reilly Media, Inc., _c2017
300			_axii, 376 páginas : _bilustraciones ; _c24 cm
336			_atxt
337			_2rdamedia _an
338			_2rdacarrier _anc
505	2		_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	4		_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			_aM. Tecnología de la información
650	1	7	_aPython (Lenguaje de programación de computadores) _2lemb _95333
650	2	0	_aLenguajes de programación _91195
650	2	7	_aMinería de datos _2lemb _94273
700	1		_aGuido, Sarah, _95321 _eaut
942			_cBK
999			_c10554 _d10554