02654nam 22006255 450 991098458950332120250226213451.09789819979929981997992710.1007/978-981-99-7992-9(MiAaPQ)EBC31924953(Au-PeEL)EBL31924953(CKB)37725746800041(DE-He213)978-981-99-7992-9(OCoLC)1505733769(EXLCZ)993772574680004120250226d2025 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAn Introduction to Materials Informatics The Elements of Machine Learning /by Tongyi Zhang1st ed. 2025.Singapore :Springer Nature Singapore :Imprint: Springer,2025.1 online resource (677 pages)9789819979912 9819979919 Introduction -- Linear Regression -- Linear Classification -- Support Vector Machine -- Decision Tree and K-Nearest-Neighbors (KNN) -- Ensemble Learning -- Bayesian Theorem and Expectation-Maximization (EM) Algorithm -- Symbolic Regression -- Neural Networks -- Hidden Markov Chains -- Data Preprocessing and Feature Selection -- Interpretative SHAP Value and Partial Dependence Plot.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.MaterialsMaterials scienceStatisticsMachine learningMaterials EngineeringMaterials ScienceApplied StatisticsMachine LearningMaterials.Materials science.Statistics.Machine learning.Materials Engineering.Materials Science.Applied Statistics.Machine Learning.620.110285631Zhang Tongyi1790170MiAaPQMiAaPQMiAaPQBOOK9910984589503321An Introduction to Materials Informatics4326262UNINA