Machine learning pure mathematics (29 risultati)
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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Paperback. Condizione: New. This book offers a focused collection of lectures and tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across the…se disciplines. Through clear conceptual explanations and practical examples, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimization and search strategies, with an in-depth look at genetic algorithms, quantum annealing, and reinforcement learning. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research.
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Da: California Books, Miami, FL, U.S.A.California Books
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 212 pages. 6.00x0.52x9.00 inches. In Stock.
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Da: California Books, Miami, FL, U.S.A.California Books
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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EUR 122,88
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Hardback. Condizione: New. This book offers a focused collection of lectures and tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across thes…e disciplines. Through clear conceptual explanations and practical examples, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimization and search strategies, with an in-depth look at genetic algorithms, quantum annealing, and reinforcement learning. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research.
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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
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Paperback. Condizione: New. This book offers a focused collection of lectures and tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across the…se disciplines. Through clear conceptual explanations and practical examples, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimization and search strategies, with an in-depth look at genetic algorithms, quantum annealing, and reinforcement learning. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 137,56
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Hardcover. Condizione: Brand New. 212 pages. 6.00x0.57x9.00 inches. In Stock.
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: California Books, Miami, FL, U.S.A.California Books
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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EUR 173,42
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.
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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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EUR 120,52
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Hardback. Condizione: New. This book offers a focused collection of lectures and tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across thes…e disciplines. Through clear conceptual explanations and practical examples, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimization and search strategies, with an in-depth look at genetic algorithms, quantum annealing, and reinforcement learning. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research.
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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EUR 216,28
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Hardback. Condizione: New. The juxtaposition of "machine learning" and "pure mathematics and theoretical physics" may first appear as contradictory in terms. The rigours of proofs and derivations in the latter seem to reside in a different world from the randomness of data and statistics in the former. Yet, an often under-apprec…iated component of mathematical discovery, typically not presented in a final draft, is experimentation: both with ideas and with mathematical data. Think of the teenage Gauss, who conjectured the Prime Number Theorem by plotting the prime-counting function, many decades before complex analysis was formalized to offer a proof.Can modern technology in part mimic Gauss's intuition? The past five years saw an explosion of activity in using AI to assist the human mind in uncovering new mathematics: finding patterns, accelerating computations, and raising conjectures via the machine learning of pure, noiseless data. The aim of this book, a first of its kind, is to collect research and survey articles from experts in this emerging dialogue between theoretical mathematics and machine learning. It does not dwell on the well-known multitude of mathematical techniques in deep learning, but focuses on the reverse relationship: how machine learning helps with mathematics. Taking a panoramic approach, the topics range from combinatorics to number theory, and from geometry to quantum field theory and string theory. Aimed at PhD students as well as seasoned researchers, each self-contained chapter offers a glimpse of an exciting future of this symbiosis.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 207,81
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Hardcover. Condizione: Brand New. 395 pages. 9.50x6.50x1.00 inches. In Stock.
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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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EUR 212,19
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Hardback. Condizione: New. The juxtaposition of "machine learning" and "pure mathematics and theoretical physics" may first appear as contradictory in terms. The rigours of proofs and derivations in the latter seem to reside in a different world from the randomness of data and statistics in the former. Yet, an often under-apprec…iated component of mathematical discovery, typically not presented in a final draft, is experimentation: both with ideas and with mathematical data. Think of the teenage Gauss, who conjectured the Prime Number Theorem by plotting the prime-counting function, many decades before complex analysis was formalized to offer a proof.Can modern technology in part mimic Gauss's intuition? The past five years saw an explosion of activity in using AI to assist the human mind in uncovering new mathematics: finding patterns, accelerating computations, and raising conjectures via the machine learning of pure, noiseless data. The aim of this book, a first of its kind, is to collect research and survey articles from experts in this emerging dialogue between theoretical mathematics and machine learning. It does not dwell on the well-known multitude of mathematical techniques in deep learning, but focuses on the reverse relationship: how machine learning helps with mathematics. Taking a panoramic approach, the topics range from combinatorics to number theory, and from geometry to quantum field theory and string theory. Aimed at PhD students as well as seasoned researchers, each self-contained chapter offers a glimpse of an exciting future of this symbiosis.
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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EUR 56,62
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Paperback. Condizione: new. Paperback. This book offers a focused collection of lectures and tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances… across these disciplines. Through clear conceptual explanations and practical examples, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimization and search strategies, with an in-depth look at genetic algorithms, quantum annealing, and reinforcement learning. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 66,65
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Paperback. Condizione: new. Paperback. This book offers a focused collection of tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across these… disciplines. Through step-by-step guidance, practical examples, and clear conceptual explanations, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimisation and search strategies, with an in-depth look at genetic algorithms and quantum annealing. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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EUR 111,70
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Hardcover. Condizione: new. Hardcover. This book offers a focused collection of tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across these… disciplines. Through step-by-step guidance, practical examples, and clear conceptual explanations, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimisation and search strategies, with an in-depth look at genetic algorithms and quantum annealing. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 93,32
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Paperback. Condizione: new. Paperback. This book offers a focused collection of tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across these… disciplines. Through step-by-step guidance, practical examples, and clear conceptual explanations, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimisation and search strategies, with an in-depth look at genetic algorithms and quantum annealing. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Hardcover. Condizione: new. Hardcover. This book offers a focused collection of tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across these… disciplines. Through step-by-step guidance, practical examples, and clear conceptual explanations, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimisation and search strategies, with an in-depth look at genetic algorithms and quantum annealing. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 146,71
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Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book offers a focused collection of lectures and tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerf…ul tools capable of driving significant advances across these disciplines. Through clear conceptual explanations and practical examples, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimization and search strategies, with an in-depth look at genetic algorithms, quantum annealing, and reinforcement learning. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research.
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Hardcover. Condizione: new. Hardcover. This book offers a focused collection of tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across these… disciplines. Through step-by-step guidance, practical examples, and clear conceptual explanations, this text equips students and researchers with the knowledge and skills needed to integrate these methods into their own work.The book begins with an introduction to the core principles of machine learning, including neural networks and transformer architectures. It then explores advanced optimisation and search strategies, with an in-depth look at genetic algorithms and quantum annealing. In the final chapters, these techniques are applied to contemporary problems in string theory and knot theory, illustrating their potential in cutting-edge research contexts. Throughout, the material is reinforced with worked examples and accompanied by code implementations to support hands-on learning.Designed for graduate students and researchers in physics and mathematics, this book serves as an accessible yet rigorous introduction to the practical use of machine learning in modern scientific research. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Da: moluna, Greven, Germaniamoluna
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Buch. Condizione: Neu. MACHINE LEARNING IN PURE MATHEMATICS AND THEORETICAL PHYSICS | He Yang-Hui | Buch | Gebunden | Englisch | 2023 | WSPC (Europe) | EAN 9781800613690 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
