Machine learning for physicists : a hands-on approach / Sadegh Raeisi, Sedighe Raeisi

Von:

Raeisi, Sadegh [VerfasserIn]

Mitwirkende(r):

Raeisi, Sedighe [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: IOP ebooks. [2023 collection]Verlag: Bristol, UK : IOP Publishing, [2023]Copyright-Datum: © 2023Beschreibung: 1 Online-Ressource (getrennte Seitenzählung) : IllustrationenISBN:

9780750349574
9780750349567

Schlagwörter:

Andere physische Formen: 9780750349550 | Erscheint auch als: Machine Learning For Physicists. Druck-Ausgabe Bristol : Institute of Physics Publishing, 2023. xiii, 1-4, 2-6, 3-90, 4-18, 5-44, 6-33, 7-21 (233) SeitenDOI: DOI: 10.1088/978-0-7503-4957-4Online-Ressourcen:

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Zusammenfassung: This book presents machine learning (ML) concepts with a hands-on approach for physicists. The goal is to both educate and enable a larger part of the community with these skills. This will lead to wider applications of modern ML techniques in physics. Accessible to physical science students, the book assumes a familiarity with statistical physics but little in the way of specialized computer science background. All chapters start with a simple introduction to the basics and the foundations, followed by some examples, and then proceeds to provide concrete examples with associated codes from a GitHub repository. Many of the code examples provided can be used as is or with suitable modification by the students for their own applications.PPN: PPN: 188318536XPackage identifier: Produktsigel: ZDB-135-IAL

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