000			01920cam a2200301zu 4500
001			88852809
003			FRCYB88852809
005			20250107224809.0
006			m o d
007			cr un
008			250107s2015 fr | o|||||0|0|||eng d
020			_a9781783987702
035			_aFRCYB88852809
040			_aFR-PaCSA _ben _c _erda
100	1		_aG., Sergio J. Rojas
245	0	1	_aLearning SciPy for Numerical and Scientific Computing - Second Edition _c['G., Sergio J. Rojas', 'Christensen, Erik A', 'Blanco-Silva, Francisco J.']
264		1	_bPackt Publishing _c2015
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aG., Sergio J. Rojas
700	0		_aChristensen, Erik A
700	0		_aBlanco-Silva, Francisco J.
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88852809 _qtext/html _a
520			_aSciPy is an open source Python library used to perform scientific computing. The SciPy (Scientific Python) package extends the functionality of NumPy with a substantial collection of useful algorithms.The book starts with a brief description of the SciPy libraries, followed by a chapter that is a fun and fast-paced primer on array creation, manipulation, and problem-solving. You will also learn how to use SciPy in linear algebra, which includes topics such as computation of eigenvalues and eigenvectors. Furthermore, the book is based on interesting subjects such as definition and manipulation of functions, computation of derivatives, integration, interpolation, and regression. You will also learn how to use SciPy in signal processing and how applications of SciPy can be used to collect, organize, analyze, and interpret data.By the end of the book, you will have fast, accurate, and easy-to-code solutions for numerical and scientific computing applications.
999			_c69089 _d69089