Name: Mechanistic Data Science for Stem Education and Applications (en Inglés)
Price: 332.21 PEN
Availability: InStock
Author: Liu, Wing Kam ; Gan, Zhengtao ; Fleming, Mark
ISBN: 9783030878344

portada Mechanistic Data Science for Stem Education and Applications (en Inglés)

Formato

Libro Físico

Autor

Editorial

Idioma

Inglés

N° páginas

276

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 1.6 cm

Peso

0.41 kg.

ISBN13

9783030878344

Categorías

Diseño de productos
Probabilidad y estadística
Ingeniería: general
Diseño técnico

Mechanistic Data Science for Stem Education and Applications (en Inglés)

Wing Kam Liu (Autor) · Zhengtao Gan (Autor) · Mark Fleming (Autor) · Springer · Tapa Blanda

Libro Físico

S/ 332,21

S/ 664,43

Ahorras: S/ 332,21

50% descuento

Envío normal

Origen: Reino Unido (Costos de importación incluídos en el precio)

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Reseña del libro "Mechanistic Data Science for Stem Education and Applications (en Inglés)"

This book introduces Mechanistic Data Science (MDS) as a structured methodology for combining data science tools with mathematical scientific principles (i.e., "mechanistic" principles) to solve intractable problems. Traditional data science methodologies require copious quantities of data to show a reliable pattern, but the amount of required data can be greatly reduced by considering the mathematical science principles. MDS is presented here in six easy-to-follow modules: 1) Multimodal data generation and collection, 2) extraction of mechanistic features, 3) knowledge-driven dimension reduction, 4) reduced order surrogate models, 5) deep learning for regression and classification, and 6) system and design. These data science and mechanistic analysis steps are presented in an intuitive manner that emphasizes practical concepts for solving engineering problems as well as real-life problems. This book is written in a spectral style and is ideal as an entry level textbook for engineering and data science undergraduate and graduate students, practicing scientists and engineers, as well as STEM (Science, Technology, Engineering, Mathematics) high school students and teachers.