Machine Learning For Physicists (ePub)
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This book presents 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 specialised 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.
Key Features:
- Practical Hands-on approach: enables the reader to use machine learning
- Includes code and accompanying online resources
- Practical examples for modern research and uses case studies
- Written in a language accessible by physics students
- Complete one-semester course
Sedighe Raeisi has a background in high-energy physics, nonlinear dynamics and chaotic systems. She holds a Ph.D. from Ferdowsi University of Mashhad where she also worked for 2 years as a lecturer after graduation. Her areas of expertise include machine learning and deep learning with special focus on Natural Language Processing (NLP), Machine Vision, Graph Neural networks and time series forecasting. She is currently working as a Data scientist in the Research and Development division of Iran's largest telecommunications company.
- Autoren: Sadegh Raeisi , Sedighe Raeisi
- 2023, 200 Seiten, Englisch
- Verlag: Institute of Physics Publishing
- ISBN-10: 0750349573
- ISBN-13: 9780750349574
- Erscheinungsdatum: 21.11.2023
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: ePub
- Größe: 15 MB
- Mit Kopierschutz
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