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Machine Learning Materials Science (58 results)
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Machine Learning in 2d Materials Science
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New.
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Machine Learning in 2D Materials Science
Language: English
Published by Taylor & Francis Ltd, 2025
ISBN 10: 0367678217 ISBN 13: 9780367678210
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Machine Learning in 2d Materials Science
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Paperback. Condition: Brand New. 248 pages. 9.18x6.12x9.21 inches. In Stock.
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Machine Learning Algorithm for Fatigue Fields in Additive Manufacturing (Werkstofftechnische Berichte ? Reports of Materials Science and Engineering)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 81.52
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Taschenbuch. Condition: Neu. Materials Data Science | Introduction to Data Mining, Machine Learning, and Data-Driven Predictions for Materials Science and Engineering | Stefan Sandfeld | Taschenbuch | The Materials Research Society Series | xxvi | Englisch | 2025 | Springer | EAN 9783031465673 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This text covers all of the data science, machine learning, and deep learning topics relevant to materials science and engineering, accompanied by numerous examples and applications. Almost all methods and algorithms introduced are implemented 'from scratch' using Python and NumPy.The book starts with an introduction to statistics and probabilities, explaining important concepts such as random variables and probability distributions, Bayes' theorem and correlations, sampling techniques, and exploratory data analysis, and puts them in the context of materials science and engineering. Therefore, it serves as a valuable primer for both undergraduate and graduate students, as well as a review for research scientists and practicing engineers. The second part provides an in-depth introduction of (statistical) machine learning. It begins with outlining fundamental concepts and proceeds to explore a variety of supervised learning techniques for regression and classification, including advanced methods such as kernel regression and support vector machines. The section on unsupervised learning emphasizes principal component analysis, and also covers manifold learning (t-SNE and UMAP) and clustering techniques. Additionally, feature engineering, feature importance, and cross-validation are introduced.The final part on neural networks and deep learning aims to promote an understanding of these methods and dispel misconceptions that they are a 'black box'. The complexity gradually increases until fully connected networks can be implemented. Advanced techniques and network architectures, including GANs, are implemented 'from scratch' using Python and NumPy, which facilitates a comprehensive understanding of all the details and enables the user to conduct their own experiments in Deep Learning.
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Condition: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
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Paperback. Condition: Brand New. 293 pages. 8.27x5.83x0.75 inches. In Stock.
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Materials Data Science : Introduction to Data Mining, Machine Learning, and Data-Driven Predictions for Materials Science and Engineering
Book 4 of 4: The Materials Research SocietyLanguage: English
Published by Springer International Publishing Mai 2024, 2024
ISBN 10: 3031465644 ISBN 13: 9783031465642
Buch. Condition: Neu. Neuware - This text covers all of the data science, machine learning, and deep learning topics relevant to materials science and engineering, accompanied by numerous examples and applications. Almost all methods and algorithms introduced are implemented 'from scratch' using Python and NumPy.The book starts with an introduction to statistics and probabilities, explaining important concepts such as random variables and probability distributions, Bayes' theorem and correlations, sampling techniques, and exploratory data analysis, and puts them in the context of materials science and engineering. Therefore, it serves as a valuable primer for both undergraduate and graduate students, as well as a review for research scientists and practicing engineers. The second part provides an in-depth introduction of (statistical) machine learning. It begins with outlining fundamental concepts and proceeds to explore a variety of supervised learning techniques for regression and classification, including advanced methods such as kernel regression and support vector machines. The section on unsupervised learning emphasizes principal component analysis, and also covers manifold learning (t-SNE and UMAP) and clustering techniques. Additionally, feature engineering, feature importance, and cross-validation are introduced.The final part on neural networks and deep learning aims to promote an understanding of these methods and dispel misconceptions that they are a 'black box'. The complexity gradually increases until fully connected networks can be implemented. Advanced techniques and network architectures, including GANs, are implemented 'from scratch' using Python and NumPy, which facilitates a comprehensive understanding of all the details and enables the user to conduct their own experiments in Deep Learning.
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Condition: As New. Unread book in perfect condition.
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Machine Learning in 2d Materials Science
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 143.13
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Machine Learning in 2D Materials Science
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 148.73
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Machine Learning in 2d Materials Science
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 149.83
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Machine Learning Applied to Composite Materials (Composites Science and Technology)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 158.32
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Machine Learning Applied to Composite Materials (Composites Science and Technology)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 158.32
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
