Norges billigste bøker

Mechanistic Data Science for STEM Education and Applications

Om Mechanistic Data Science for STEM Education and Applications

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 leveltextbook 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.

Vis mer
  • Språk:
  • Engelsk
  • ISBN:
  • 9783030878344
  • Bindende:
  • Paperback
  • Sider:
  • 292
  • Utgitt:
  • 23 desember 2022
  • Utgave:
  • 22001
  • Dimensjoner:
  • 155x16x235 mm.
  • Vekt:
  • 446 g.
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 15 oktober 2024

Beskrivelse av Mechanistic Data Science for STEM Education and Applications

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 leveltextbook 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.

Brukervurderinger av Mechanistic Data Science for STEM Education and Applications



Finn lignende bøker
Boken Mechanistic Data Science for STEM Education and Applications finnes i følgende kategorier:

Gjør som tusenvis av andre bokelskere

Abonner på vårt nyhetsbrev og få rabatter og inspirasjon til din neste leseopplevelse.