000			01933cam a22002777i 4500
001			TB11231
003			IN-BhIIT
005			20240306193035.0
008			170710t20162017caua 001 0 eng d
020			_a9789352134571
040			_aIN-BhIIT
041			_aeng
082	0	4	_a005.133 _bMUL/I
100	1		_aMuller, Andreas C., _eAuthor _922414
245	1	0	_aIntroduction to machine learning with Python : _ba guide for data scientists / _cby Andreas C. Müller and Sarah Guido.
260			_aMumbai : _bO'Reilly, _bSPD Pvt. Ltd., _c2019.
300			_axii, 376 p. : _bill. ; _c24 cm
504			_aIncluding bibliographical references and 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	_aMachine learning _xProgramming languages (Electronic computers). _922415
650		0	_aPython (Computer program language). _92578
650		0	_aData mining.
700	1		_aGuido, Sarah, _eJoint author. _922416
942			_cTB _01
999			_c13683 _d13683