Wing Kam Liu,Zhengtao Gan,Mark Fleming
Mechanistic Data Science for STEM Education and Applications
Mechanistic Data Science for STEM Education and Applications
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- More about Mechanistic Data Science for STEM Education and Applications
Mechanistic Data Science (MDS) is a structured methodology for combining data science tools with mathematical scientific principles to solve intractable problems, presented in six easy-to-follow modules. It is ideal for undergraduate and graduate students, practicing scientists and engineers, and STEM high school students and teachers.
Format: Hardback
Length: 276 pages
Publication date: 22 December 2021
Publisher: Springer Nature Switzerland AG
Mechanistic Data Science (MDS) is a structured methodology for combining data science tools with mathematical scientific principles to solve intractable problems. It introduces six easy-to-follow modules: multimodal data generation and collection, extraction of mechanistic features, knowledge-driven dimension reduction, reduced order surrogate models, deep learning for regression and classification, and system and design. These data science and mechanistic analysis steps are presented in an intuitive manner that emphasizes practical concepts for solving engineering problems and real-life problems. The 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, STEM high school students and teachers.
Weight: 659g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030878313
Edition number: 1st ed. 2021
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