000			01577nam a22002177a 4500
999			_c4500 _d4500
005			20230117113005.0
008			230117b ||||| |||| 00| 0 eng d
020			_a9780367027056
082			_a515 _bCAR
245			_aData science for mathematicians
260			_bCRC Press _aBoco Raton _c2021
300			_axv, 528 p.
365			_aGBP _b140.00
504			_aTable of Contents Contents Chapter 1 Introduction 1 Chapter 2 Programming with Data Chapter 3 Linear Algebra Chapter 4 Basic Statistics Chapter 5 Clustering Chapter 6 Operations Research Chapter 7 Dimensionality Reduction Chapter 8 Machine Learning Chapter 9 Deep Learning Chapter 10 Topological Data Analysis Bibliography
520			_aMathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science. As it applies to the curriculum, research, and career opportunities, data science is a fast-growing field. Contributors from both academics and industry present their views on these opportunities and how to advantage them.
650			_aMathematical analysis _96337
650			_aMathematical statistics _9837
650			_aData mining _9365
700			_aCarter, Nathan _910503
942			_2ddc _cBK