000			02145nam a22002177a 4500
008			240424b |||||||| |||| 00| 0 eng d
020			_a9781108472449
040			_cTBS
041			_aeng
050			_aQA76 _b.S469 2020
100			_aShah, Chirag _923374 _eauthor
245			_aA hands-on introduction to data science _c/ Chirag Shah.
260			_aCambridge ; New York, NY, : Cambridge University Press, 2020.
300			_axxiii, 433 pages : illustrations, charts, tables (some color) ; 26 cm.
504			_aIncludes bibliographical references and index.
505			_aPt. 1. Conceptual introductions — 1. Introduction — 2. Data — 3. Techniques — Pt. 2. Tools for data science — 4. UNIX — 5. Python — 6. R — 7. MySQL — Pt. 3. Machine learning for data science — 8. Machine learning introduction and regression — 9. Supervised learning — 10. Unsupervised learning — Pt. 4. Applications, evaluations, and methods — 11. Hands-on with solving data problems — 12. Data collection, experimentation and evaluation.
520			_aThis book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science.
650		0	_aComputer science _911917
650		0	_aInformation technology _93592
942			_2lcc
999			_c4058 _d4058