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Cover: 9781316512821 | Machine Learning for Engineers | Simeone Osvaldo | Buch | Englisch
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Machine Learning for Engineers
Buch von Simeone Osvaldo
Sprache: Englisch

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Beschreibung
All stars are known to power strong stellar winds at the end of their lives, expelling stellar material that is recycled as building blocks of new planets and life. IAU S366 provides an overview of state-of-the-art observational, theoretical and numerical studies on the origin of winds in evolved stars.
All stars are known to power strong stellar winds at the end of their lives, expelling stellar material that is recycled as building blocks of new planets and life. IAU S366 provides an overview of state-of-the-art observational, theoretical and numerical studies on the origin of winds in evolved stars.
Über den Autor
Osvaldo Simeone is a Professor of Information Engineering at King's College London, where he directs King's Communications, Learning & Information Processing (KCLIP) lab. He is a Fellow of the IET and IEEE.
Inhaltsverzeichnis
Part I. Introduction and Background: 1. When and how to use machine learning; 2. Background. Part II. Fundamental Concepts and Algorithms: 3. Inference, or model-driven prediction; 4. Supervised learning: getting started; 5. Optimization for machine learning; 6. Supervised learning: beyond least squares; 7: Unsupervised learning. Part III. Advanced Tools and Algorithms: 8. Statistical learning theory; 9. Exponential family of distributions; 10. Variational inference and variational expectation maximization; 11. Information-theoretic inference and learning; 12. Bayesian learning. Part IV. Beyond Centralized Single-Task Learning: 13. Transfer learning, multi-task learning, continual learning, and meta-learning; 14. Federated learning. Part V. Epilogue: 15. Beyond this book.
Details
Erscheinungsjahr: 2022
Fachbereich: Fertigungstechnik
Genre: Technik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781316512821
ISBN-10: 1316512827
Sprache: Englisch
Einband: Gebunden
Autor: Osvaldo, Simeone
Auflage: New ed
Hersteller: Cambridge University Pr.
Abbildungen: Worked examples or Exercises
Maße: 260 x 208 x 37 mm
Von/Mit: Simeone Osvaldo
Erscheinungsdatum: 31.08.2022
Gewicht: 1,629 kg
Artikel-ID: 121298955
Über den Autor
Osvaldo Simeone is a Professor of Information Engineering at King's College London, where he directs King's Communications, Learning & Information Processing (KCLIP) lab. He is a Fellow of the IET and IEEE.
Inhaltsverzeichnis
Part I. Introduction and Background: 1. When and how to use machine learning; 2. Background. Part II. Fundamental Concepts and Algorithms: 3. Inference, or model-driven prediction; 4. Supervised learning: getting started; 5. Optimization for machine learning; 6. Supervised learning: beyond least squares; 7: Unsupervised learning. Part III. Advanced Tools and Algorithms: 8. Statistical learning theory; 9. Exponential family of distributions; 10. Variational inference and variational expectation maximization; 11. Information-theoretic inference and learning; 12. Bayesian learning. Part IV. Beyond Centralized Single-Task Learning: 13. Transfer learning, multi-task learning, continual learning, and meta-learning; 14. Federated learning. Part V. Epilogue: 15. Beyond this book.
Details
Erscheinungsjahr: 2022
Fachbereich: Fertigungstechnik
Genre: Technik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781316512821
ISBN-10: 1316512827
Sprache: Englisch
Einband: Gebunden
Autor: Osvaldo, Simeone
Auflage: New ed
Hersteller: Cambridge University Pr.
Abbildungen: Worked examples or Exercises
Maße: 260 x 208 x 37 mm
Von/Mit: Simeone Osvaldo
Erscheinungsdatum: 31.08.2022
Gewicht: 1,629 kg
Artikel-ID: 121298955
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