Using a novel integration of mathematics and Python codes, this book illustrates the fundamental concepts that link probability, statistics, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also…
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This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cádiz (Spain) between June 11–16 2014, and sponsored by the American Statistical Association, the Institute of Mathematic…
This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms. Another feature of the book is that it emphasizes what model underlies a procedure and what objective function is optimized for fitting th…
This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provid…
This essential textbook presents a concise introduction to the fundamental principles of software engineering, together with practical guidance on how to apply the theory in a real-world, industrial environment. The wide-ranging coverage encompasses all areas of software design,…
Offering a unique learn-by-doing approach, this hands-on book will help you sharpen your skills by applying them in the context of projects with R, including dashboards, image processing, data reduction, mapping, and more. --
Introduces new and advanced methods of model discovery for time-series data using artificial intelligence.Implements topological approaches to distill "machine-intuitive" models from complex dynamics data.Introduces a new paradigm for a parsimonious model of a dynamical system w…
"Dealing with artificial intelligence, this book delineates AI's role in model discovery for dynamical systems. With the implementation of topological methods to construct metamodels, it engages with levels of complexity and multi-scale hierarchies hitherto considered off limits…
STEM Problems with Mathcad and Python
by Stevens, Alan, Ochkov, Valery, Tikhonov, Anton
0
Type: Book
Features Suitable for undergraduates and early postgraduates who need simple and accessible guidance for solving practical interdisciplinary technical problems Can be used as an additional textbook in a variety of topics, including Calculus, Linear Algebra, Analytical Geometry, …
STEM Problems with Mathcad and Python seeks to remove the fear of tackling difficult scientific and technical calculations for future mathematicians, engineers, scientists, and other STEM researchers. The authors hope to show that such calculations can be not only useful, but th…
This book offers solutions to all 284 exercises in Advanced R, Second Edition. All the solutions have been carefully documented and made to be as clear and accessible as possible. Working through the exercises and their solutions will give you a deeper understanding of a variety…
This book constitutes the refereed proceedings of the 16th International Workshop on Algorithms in Bioinformatics, WABI 2016, held in Aarhus, Denmark. The 25 full papers together with 2 invited talks presented were carefully reviewed and selected from 54 submissions. The selecte…
