Jeffrey P Advance Python for Data Science 2024 | 586.52 KB
89 Pages
Title: Advance python for data science
Author: Pat v. Jeffrey
Description:
Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection.
Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection.
DOWNLOAD:
rapidgator.net/file/0df3c7da63b8262081f48985cd7fdcfe/Jeffrey_P._Advance_Python_for_Data_Science_2024.pdf
k2s.cc/file/54e7a7b69330b/Jeffrey_P._Advance_Python_for_Data_Science_2024.pdf