Additive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4

Additive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4
Author: Sharlotte L. B. Kramer
Publisher: Springer Nature
Total Pages: 101
Release:
Genre:
ISBN: 3031504747


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Additive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4
Language: en
Pages: 101
Authors: Sharlotte L. B. Kramer
Categories:
Type: BOOK - Published: - Publisher: Springer Nature

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Thermomechanics & Infrared Imaging, Inverse Problem Methodologies, Mechanics of Additive & Advanced Manufactured Materials, and Advancements in Optical Methods & Digital Image Correlation, Volume 4
Language: en
Pages: 109
Authors: Sharlotte L.B. Kramer
Categories: Technology & Engineering
Type: BOOK - Published: 2022-02-14 - Publisher: Springer Nature

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Thermomechanics & Infrared Imaging, Inverse Problem Methodologies and Mechanics of Additive & Advanced Manufactured Materials, and Advancement of Optical Method
Smart Materials in Additive Manufacturing, volume 2: 4D Printing Mechanics, Modeling, and Advanced Engineering Applications
Language: en
Pages: 466
Authors: Mahdi Bodaghi
Categories: Technology & Engineering
Type: BOOK - Published: 2022-06-25 - Publisher: Elsevier

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Smart Materials in Additive Manufacturing, Volume 2 covers the mechanics, modeling, and applications of the technology and the materials produced by it. It appr
Automated Machine Learning
Language: en
Pages: 223
Authors: Frank Hutter
Categories: Computers
Type: BOOK - Published: 2019-05-17 - Publisher: Springer

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This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing sys
Materials Discovery and Design
Language: en
Pages: 266
Authors: Turab Lookman
Categories: Science
Type: BOOK - Published: 2018-09-22 - Publisher: Springer

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This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning fr