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Designed for engineers, mathematicians, computer scientists, financial analysts, and anyone interested in using numerical linear algebra, matrix theory, and game... Læs mere
Readers must visit the HTML version of each chapter and access the Electronic Supplementary Material. Extras for Appendices A & B can be found in Extras for Chapter 18.
The conference examines the historical roots and expansive potential of computation and... Læs mere
The conference examines the historical roots and expansive potential of computation and... Læs mere
Bayesian inference uses probability distributions and Bayes' theorem to build flexible models. The book uses PyMC3 to abstract all the mathematical and computational details from this process allowing readers to solve a wide range of problems in data science.
Discrete math deals with studying finite and distinct elements. With this... Læs mere
Contains papers that represent the proceedings of the DIMACS workshop on 'Feasible Arithmetics and Proof Complexity' held in April 1996 at Rutgers University in... Læs mere