000			01842cam a22003615i 4500
999			_c28232 _d28203
001			21347569
003			EG-ScBUE
005			20200304151653.0
008			191230s2019 cc a f b 001 0 eng d
020			_a9781492041139
035			_a(OCoLC)on1060198620
040			_aYDX _beng _erda _cYDX _dBDX _dOCLCQ _dBYV _dOCP _dCLE _dJRZ _dOCLCF _dTVG _dVU@ _dYDXIT _dHF9 _dDLC _dEG-ScBUE
082	0	4	_a005.7565 _bGRU _222
100	1		_aGrus, Joel _c(Software engineer), _eauthor.
245	1	0	_aData science from scratch : _bfirst principles with Python / _cJoel Grus.
250			_aSecond edition.
264		1	_aBeijing ; _aSebastopol, CA _bO'Reilly Media, _c2019.
300			_axvii, 384 pages : _billustrations ; _c24 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
505	0		_aIntroduction -- A crash course in Python -- Visualizing data -- Linear algebra -- Statistics -- Probability -- Hypothesis and inference -- Gradient descent -- Getting data -- Working with data -- Machine learning -- k-Nearest neighbors -- Naive bayes -- Simple linear regression -- Multiple regression -- Logistic regression -- Decision trees -- Neural networks -- Deep learning -- Clustering -- Natural language processing -- Network analysis -- Recommender systems -- Databases and SQL -- MapReduce -- Data ethics -- Go forth and do data science.
650		7	_aPython (Computer program language) _2BUEsh
650		7	_aDatabase management. _2BUEsh
650		7	_aData structures (Computer science) _2BUEsh
650		7	_aData mining. _2BUEsh
650		7	_aData mining _xMathematics. _2BUEsh
653			_bCOMSCI _cMarch2020
655			_vText book _933728
942			_2ddc _cBB