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Englisch
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Beschreibung
A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.
This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning.
Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.
This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning.
Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.
A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.
This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning.
Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.
This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning.
Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.
Details
| Erscheinungsjahr: | 2021 |
|---|---|
| Fachbereich: | Astronomie |
| Genre: | Importe, Physik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Inhalt: | Gebunden |
| ISBN-13: | 9789811237454 |
| ISBN-10: | 981123745X |
| Sprache: | Englisch |
| Ausstattung / Beilage: | HC gerader Rücken kaschiert |
| Einband: | Gebunden |
| Autor: | Martin Erdmann, Jonas Glombitza Gregor |
| Hersteller: | World Scientific |
| Verantwortliche Person für die EU: | Books on Demand GmbH, In de Tarpen 42 In de Tarpen 42, D-22848 Norderstedt, info@bod.de |
| Maße: | 235 x 157 x 23 mm |
| Von/Mit: | Jonas Glombitza Gregor Martin Erdmann |
| Erscheinungsdatum: | 15.06.2021 |
| Gewicht: | 0,644 kg |
Details
| Erscheinungsjahr: | 2021 |
|---|---|
| Fachbereich: | Astronomie |
| Genre: | Importe, Physik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Inhalt: | Gebunden |
| ISBN-13: | 9789811237454 |
| ISBN-10: | 981123745X |
| Sprache: | Englisch |
| Ausstattung / Beilage: | HC gerader Rücken kaschiert |
| Einband: | Gebunden |
| Autor: | Martin Erdmann, Jonas Glombitza Gregor |
| Hersteller: | World Scientific |
| Verantwortliche Person für die EU: | Books on Demand GmbH, In de Tarpen 42 In de Tarpen 42, D-22848 Norderstedt, info@bod.de |
| Maße: | 235 x 157 x 23 mm |
| Von/Mit: | Jonas Glombitza Gregor Martin Erdmann |
| Erscheinungsdatum: | 15.06.2021 |
| Gewicht: | 0,644 kg |
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