000			01311nam a2200217 4500
005			20250711174917.0
008			250711b |||||||| |||| 00| 0 eng d
020			_a9783662678817
082			_a006.312 PLA _bPLA
100			_aPlaue, Matthias
245			_aData science _b: an introduction to statistics and machine learning
260			_aGermany: _bSpringer Nature, _c2023.
300			_axxiv, 361p.
500			_aIncludes bibliographical references and index.
520			_aThis textbook provides an easy-to-understand introduction to the mathematical concepts and algorithms at the foundation of data science. It covers essential parts of data organization, descriptive and inferential statistics, probability theory, and machine learning. These topics are presented in a clear and mathematical sound way to help readers gain a deep and fundamental understanding. Numerous application examples based on real data are included. The book is well-suited for lecturers and students at technical universities, and offers a good introduction and overview for people who are new to the subject. Basic mathematical knowledge of calculus and linear algebra is required.
650			_aData modeling
650			_aStatistics
650			_aProbability
650			_aMachine learning
942			_2ddc _n0 _cC
999			_c30518 _d30518