Experimental Design for Data Science and Engineering

Theory, experiments, computation, and data are considered as the four pillars of science and engineering. Experimental Design for Data Science and Engineering describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from d...

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Hlavní autor:	Joseph, V. Roshan
Médium:	Online
Jazyk:	angličtina
Vydáno:	Taylor & Francis 2025
Témata:	computer experiments Gaussian process modeling Design of Experiments uncertainty quantification Monte Carlo simulation sensitivity analysis fractional factorial methods R and Python examples robust experimental design techniques thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes
On-line přístup:	ONIX_20251218T105429_9781040749319_4
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!