000			01357nam a2200229 4500
005			20250630163835.0
008			250627b |||||||| |||| 00| 0 eng d
020			_a 9781032941752
040			_aCSL _cCSL
041			_2eng _aeng
084			_aB28 R0 _qCSL
245			_aStatistical foundations of data science
260			_aBoca Raton : _bCRC Press, _c2020.
300			_axxi, 752p. _b: ill. _c; 24 cm.
500			_aIncludes reference and index
520			_a Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis.
650			_aMachine learning _9480917
650			_aRegression analysis _9732722
650			_aHigh-dimensional data analysis _9814857
700			_aFan, Jianqing _eauthor.
942			_2CC _n0 _cTEXL _hB28 R0
999			_c1433089 _d1433089