Data science for mathematicians
- Boca Raton : CRC Press, 2020
- xv, 528 p. ; ill., 25 cm
- CRC Press/Chapman and Hall Handbooks in Mathematics Series .
Includes bibliographical references and index.
Mathematicians 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.
9780367027056
Mathematical analysis Mathematical statistics Data mining Big data Mathematics Data Science Regression assumptions Backpropagation Bayes' formula Central Limit Theorem Density-based methods Hierarchical clustering K-means results Bootsrap resampling Multilayer perceptrons Feature selection Decision trees Logistic regression SVD Nonlinear Principal Component Analysis Optimization Simulation Persistent homology QR decompositions Topological Data Analysis Deep earning Machine learning