000			04077nam a2200481Mi 4500
005			20250918233659.0
008			140815s2013 enkad 001 0 eng
020			_a9781782161622 _cRM103.46
020			_a1782161627
039		9	_a201408180922 _brosli _c201408151540 _drosli _c201408121111 _dbinar _y03-19-2014 _zbinar
040			_aAU@ _beng _cAU@ _erda _dYDXCP _dKHN _dOCLCO _dUKM
090			_aQA76.6.B574 3
090			_aQA76.6 _b.B574 3
100	1		_aBlanco-Silva, Francisco J., _eauthor.
245	1	0	_aLearning SciPy for numerical and scientific computing : _ba practical tutorial that guarantees fast, accurate, and easy-to-code solutions to your numerical adn scientific computing problems with the power of SciPy and Python / _cFrancisco Blanco-Silva.
246	3	0	_aLearning SciPy for numerical and scientific computing
260			_aBirmingham, UK _bPackt Pubublishing, _c2013.
300			_a136 pages : _billustrations, charts, graphs ; _c24 cm.
336			_atext _2rdacontent
336			_astill image _2rdacontent
337			_aunmediated _2rdamedia
338			_avolume _2rdacarrier
490	1		_aCommunity experience distilled
500			_aIncludes index.
500			_aSubtitle from cover.
505	0		_aChapter 1: Introduction to SciPy -- Chapter 2: Top-level SciPy -- Chapter 3: SciPy for Linear Algebra -- Chapter 5: SciPy for Signal Processing -- Chapter 6: SciPy for Data Mining -- Chapter 7: SciPy for Computational Geometry -- Chapter 8: Interaction with Other Languages -- Index.
520			_aIt's essential to incorporate workflow data and code from various sources in order to create fast and effective algorithms to solve complex problems in science and engineering. Data is coming at us faster, dirtier, and at an ever increasing rate. There is no need to employ difficult-to-maintain code, or expensive mathematical engines to solve your numerical computations anymore. SciPy guarantees fast, accurate, and easy-to-code solutions to your numerical and scientific computing applications.
520	8		_a'Learning SciPy for Numerical and Scientific Computing' unveils secrets to some of the most critical mathematical and scientific computing problems and will play an instrumental role in supporting your research. The book will teach you how to quickly and efficiently use different modules and routines from the SciPy library to cover the vast scope of numerical mathematics with its simplistic practical approach that's easy to follow.
520	8		_aThe book starts with a brief description of the SciPy libraries, showing practical demonstrations for acquiring and installing them on your system. This is followed by the second chapter which is a fun and fast-paced primer to array creation, manipulation, and problem-solving based on these techniques.
520	8		_aThe rest of the chapters describe the use of all different modules and routines from the SciPy libraries, through the scope of different branches of numerical mathematics. Each big field is represented: numerical analysis, linear algebra, statistics, signal processing, and computational geometry. And for each of these fields all possibilities are illustrated with clear syntax, and plenty of examples. The book then presents combinations of all these techniques to the solution of research problems in real-life scenarios for different sciences or engineering - from image compression, biological classification of species, control theory, design of wings, to structural analysis of oxides.
650		0	_aPython (Computer program language)
650		0	_aNumerical analysis _xData processing.
650		0	_aNumerical analysis.
830		0	_aCommunity experience distilled.
907			_a.b15850912 _b2019-11-12 _c2019-11-12
942			_c01 _n0 _kQA76.6.B574 3
914			_avtls003553932
990			_ark4
991			_aFakulti Teknologi dan Sains Maklumat
998			_al _b2014-06-03 _cm _da _feng _genk _y0 _z.b15850912
999			_c565017 _d565017