000			03344cam a22004098i 4500
001			22930157
003			UNISSA
005			20240420142135.0
008			230114s2023 flu b 001 0 eng
010			_a 2022057798
020			_a9781032258737
020			_a9781032258713
020			_z9781003285816
040			_aDLC _beng _erda _cDLC _dUNISSA
042			_apcc
050	0	0	_aQA76.73.P98 _bL96 2023
100	1		_aLynch, Stephen, _d1964- _eauthor.
245	1	0	_aPython for scientific computation and artificial intelligence / _cStephen Lynch.
250			_aFirst edition.
263			_a2304
264		1	_aBoca Raton : _bC&H/CRC Press, _c2023.
300			_apages cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
490	0		_aChapman & Hall/CRC the Python series
504			_aIncludes bibliographical references and index.
505	0		_aThe idle integrated development learning environment -- Anaconda, Spyder and the Libraries Numpy, Matplotlib and Sympy -- Jupyter Notebooks and Google Colab -- Python for AS-level (high school) mathematics -- Python for A-level (high school) mathematics -- Biology -- Chemistry -- Data science -- Economics -- Engineering -- Fractals and multifractals -- Image processing -- Numerical methods for ordinary and partial differential equations -- Physics -- Statistics -- Brain inspired computing -- Neural networks and neurodynamics -- Tensorflow and keras -- Recurrent neural networks -- Convolutional neural networks, tensorboard, and further reading -- Answers and hints to exercises.
520			_a"Python for Scientific Computation and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web"-- _cProvided by publisher.
650		0	_aPython (Computer program language)
650		0	_aScience _xData processing.
650		0	_aArtificial intelligence.
776	0	8	_iOnline version: _aLynch, Stephen, 1964- _tPython for scientific computation and artificial intelligence. _bFirst edition _dBoca Raton : C&H/CRC Press, 2023 _z9781003285816 _w(DLC) 2022057799
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2lcc _cQ-R
999			_c35870 _d35870