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Cover: 9781108494939 | Machine Learning with Neural Networks | Bernhard Mehlig | Buch | 2022
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Machine Learning with Neural Networks
An Introduction for Scientists and Engineers
Buch von Bernhard Mehlig
Sprache: Englisch

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Beschreibung
Modern introduction to machine learning with neural networks. Key principles of the topic are described alongside cutting-edge applications.
Modern introduction to machine learning with neural networks. Key principles of the topic are described alongside cutting-edge applications.
Über den Autor
Bernhard Mehlig is Professor in Physics at the University of Gothenburg, Sweden. His research is focused on statistical physics of complex systems, and he has published extensively in this area. In 2010, he was awarded the prestigious Göran Gustafsson prize in physics for his outstanding research in statistical physics. He has taught a course on machine learning for more than 15 years at the University of Gothenburg.
Inhaltsverzeichnis
Acknowledgements. 1. Introduction. Part I. Hopfield Networks: 2. Deterministic Hopfield networks; 3. Stochastic Hopfield networks; 4. The Boltzmann distribution. Part II. Supervised Learning: 5. Perceptrons; 6. Stochastic gradient descent; 7. Deep learning; 8. Convolutional networks; 9. Supervised recurrent networks. Part III. Learning Without Labels: 10. Unsupervised learning; 11. Reinforcement learning. Bibliography. Author Index. Index.
Details
Erscheinungsjahr: 2022
Fachbereich: Astronomie
Genre: Importe, Physik
Rubrik: Naturwissenschaften & Technik
Thema: Lexika
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781108494939
ISBN-10: 1108494935
Sprache: Englisch
Einband: Gebunden
Autor: Mehlig, Bernhard
Hersteller: Cambridge University Pr.
Verantwortliche Person für die EU: Produktsicherheitsverantwortliche/r, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Abbildungen: Worked examples or Exercises
Maße: 250 x 176 x 18 mm
Von/Mit: Bernhard Mehlig
Erscheinungsdatum: 14.02.2022
Gewicht: 0,654 kg
Artikel-ID: 120325576
Über den Autor
Bernhard Mehlig is Professor in Physics at the University of Gothenburg, Sweden. His research is focused on statistical physics of complex systems, and he has published extensively in this area. In 2010, he was awarded the prestigious Göran Gustafsson prize in physics for his outstanding research in statistical physics. He has taught a course on machine learning for more than 15 years at the University of Gothenburg.
Inhaltsverzeichnis
Acknowledgements. 1. Introduction. Part I. Hopfield Networks: 2. Deterministic Hopfield networks; 3. Stochastic Hopfield networks; 4. The Boltzmann distribution. Part II. Supervised Learning: 5. Perceptrons; 6. Stochastic gradient descent; 7. Deep learning; 8. Convolutional networks; 9. Supervised recurrent networks. Part III. Learning Without Labels: 10. Unsupervised learning; 11. Reinforcement learning. Bibliography. Author Index. Index.
Details
Erscheinungsjahr: 2022
Fachbereich: Astronomie
Genre: Importe, Physik
Rubrik: Naturwissenschaften & Technik
Thema: Lexika
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781108494939
ISBN-10: 1108494935
Sprache: Englisch
Einband: Gebunden
Autor: Mehlig, Bernhard
Hersteller: Cambridge University Pr.
Verantwortliche Person für die EU: Produktsicherheitsverantwortliche/r, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Abbildungen: Worked examples or Exercises
Maße: 250 x 176 x 18 mm
Von/Mit: Bernhard Mehlig
Erscheinungsdatum: 14.02.2022
Gewicht: 0,654 kg
Artikel-ID: 120325576
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