An introduction to materials informatics: the elements of machine learning

By:

Zhang, Tongyi

Material type: Text

TextPublication details: Singapore Springer 2025Description: xvi,479 pISBN:

9789819979912

Subject(s):

DDC classification:

006.31 ZHA

Summary: This textbook educates current and future materials workers, engineers, and researchers on Materials Informatics. Volume I serves as an introduction, merging AI, ML, materials science, and engineering. It covers essential topics and algorithms in 11 chapters, including Linear Regression, Neural Networks, and more. Suitable for diverse fields like materials science, physics, and chemistry, it enables quick and easy learning of Materials Informatics for readers without prior AI and ML knowledge. (https://link.springer.com/book/10.1007/978-981-99-7992-9)

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	IT & Decisions Sciences	006.31 ZHA (Browse shelf(Opens below))	1	Available		009186

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Previous	006.31 VIS Time series forecasting using generative AI: leveraging AI for precision forecasting	006.31 WIC Machine learning:	006.31 YE Modern deep learning for tabular data: novel approaches to common modeling problems	006.31 ZHA An introduction to materials informatics: the elements of machine learning	006.31015192 MUR Probabilistic machine learning: advanced topics	006.312 AGG Data mining: the textbook	006.312 AND Doing data science in R:	Next

Table of contents:
Front Matter
Pages i-xvi
Download chapter PDF
Introduction
Tongyi Zhang
Pages 1-12
Linear Regression
Tongyi Zhang
Pages 13-51
Linear Classification
Tongyi Zhang
Pages 53-83
Support Vector Machine
Tongyi Zhang
Pages 85-116
Decision Tree and K-Nearest-Neighbors (KNN)
Tongyi Zhang
Pages 117-140
Ensemble Learning
Tongyi Zhang
Pages 141-165
Bayesian Theorem and Expectation–Maximization (EM) Algorithm
Tongyi Zhang
Pages 167-228
Symbolic Regression
Tongyi Zhang
Pages 229-244
Neural Networks
Tongyi Zhang
Pages 245-323
Hidden Markov Chains
Tongyi Zhang
Pages 325-361
Data Preprocessing and Feature Selection
Tongyi Zhang
Pages 363-427
Interpretative SHAP Value and Partial Dependence Plot
Tongyi Zhang
Pages 429-462
Back Matter
Pages 463-479

[https://link.springer.com/book/10.1007/978-981-99-7992-9]

This textbook educates current and future materials workers, engineers, and researchers on Materials Informatics. Volume I serves as an introduction, merging AI, ML, materials science, and engineering. It covers essential topics and algorithms in 11 chapters, including Linear Regression, Neural Networks, and more. Suitable for diverse fields like materials science, physics, and chemistry, it enables quick and easy learning of Materials Informatics for readers without prior AI and ML knowledge.

(https://link.springer.com/book/10.1007/978-981-99-7992-9)

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