000			01981cam a2200313 i 4500
001			19327583
003			KeNaZET
005			20230718101416.0
008			161005s2017 njua bf 001 0 eng
010			_a 2016043329
020			_a9781119092940
040			_aZET-ke _beng _cZET-ke _dZET-ke
050	0	0	_aQA76.9.D32 _bC33 2017
100	1		_aCady, Field, _d1984
245	1	4	_aThe data science handbook / _cby Field Cady.
260			_aHoboken: _bWiley, _cc2017
300			_axviii, 396 pages : _bill. _c24 cm
500			_aIncludes Bibliographies Index.
504			_aIncludes bibliographical references and index.
505			_rIntroduction: Becoming unicorn -- Data science road map -- programming languages -- my personal toolkit -- Visualizations and simple metrics -- machine learning overview -- Interlude: feature extraction ideas -- Technical communication and documentation -- Unsupervised learning: clustering and dimensionality reduction -- Regression -- Data encodings and file formats -- Big data -- Databases -- Software engineering best practices -- Natural language processing -- Time series analysis -- Probability -- Statistics -- Programming language concepts -- performance and computer memory -- Computer and data structures -- Maximum likelihood estimation and optimization -- Advances classifiers -- stochastic modelling.
650		0	_aDatabases _vHandbooks, manuals, etc.
650		0	_aStatistics _xData processing _vHandbooks, manuals, etc.
650		0	_aBig data _vHandbooks, manuals, etc.
650		0	_aInformation theory _vHandbooks, manuals, etc.
776	0	8	_iOnline version: _aCady, Field, 1984- author. _tData science handbook _dHoboken, NJ : John Wiley & Sons, Inc., 2017 _z9781119092933 _w(DLC) 2016046263
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2lcc _cBK _hQA76.9.D32 _i.C33 2017 _kQA76.9.D32 _m.C33 2017
999			_c5409 _d5409