Verlag: Cambridge University Press, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
Sprache: Englisch
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Verlag: Cambridge University Press, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
Sprache: Englisch
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Verlag: Cambridge University Press, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
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Verlag: Cambridge University Press, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
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Verlag: Cambridge University Press, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
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Verlag: Cambridge University Press CUP, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
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Verlag: Cambridge University Press, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
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ISBN 10: 1108845355 ISBN 13: 9781108845359
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In den WarenkorbZustand: New. This is the first rigorous, self-contained treatment of the theory of deep learning. Aimed at scientists, instructors, and students interested in artificial intelligence and deep learning, it demonstrates many applications in physics, chemistry, and biomedi.
Verlag: Cambridge University Press, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
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In den WarenkorbHardback. Zustand: New. New copy - Usually dispatched within 4 working days. 911.
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ISBN 10: 1108845355 ISBN 13: 9781108845359
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In den WarenkorbHardcover. Zustand: Brand New. 371 pages. 9.75x7.00x1.00 inches. In Stock.
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ISBN 10: 1108845355 ISBN 13: 9781108845359
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ISBN 10: 1108845355 ISBN 13: 9781108845359
Sprache: Englisch
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ISBN 10: 1108845355 ISBN 13: 9781108845359
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In den WarenkorbHardcover. Zustand: new. Hardcover. This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking. This is the first rigorous, self-contained treatment of the theory of deep learning. Aimed at scientists, instructors, and students interested in artificial intelligence and deep learning, it demonstrates many applications in physics, chemistry, and biomedicine. It includes a full set of exercises and encourages out-of-the-box thinking. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Verlag: Cambridge University Press Jul 2021, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
Sprache: Englisch
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In den WarenkorbBuch. Zustand: Neu. Neuware - Rigorous treatment of the theory of deep learning from first principles, with applications to beautiful problems in the natural sciences.
Verlag: Cambridge University Press, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: Brand New. 371 pages. 9.75x7.00x1.00 inches. In Stock.
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ISBN 10: 1108845355 ISBN 13: 9781108845359
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking. This is the first rigorous, self-contained treatment of the theory of deep learning. Aimed at scientists, instructors, and students interested in artificial intelligence and deep learning, it demonstrates many applications in physics, chemistry, and biomedicine. It includes a full set of exercises and encourages out-of-the-box thinking. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Verlag: Cambridge University Press, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
Sprache: Englisch
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Verlag: Cambridge University Press, Cambridge, 2021
ISBN 10: 1108845355 ISBN 13: 9781108845359
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking. This is the first rigorous, self-contained treatment of the theory of deep learning. Aimed at scientists, instructors, and students interested in artificial intelligence and deep learning, it demonstrates many applications in physics, chemistry, and biomedicine. It includes a full set of exercises and encourages out-of-the-box thinking. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.