Deep learning in science:
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 o...
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cambridge
Cambridge University Press
2021
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Schlagworte: | |
Online-Zugang: | BSB01 FHN01 TUM01 Volltext |
Zusammenfassung: | 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 |
Beschreibung: | Title from publisher's bibliographic system (viewed on 22 Feb 2021) |
Beschreibung: | 1 Online-Ressource (xiv, 371 Seiten) |
ISBN: | 9781108955652 |
DOI: | 10.1017/9781108955652 |
Internformat
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Datensatz im Suchindex
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discipline | Pädagogik Biologie Informatik |
discipline_str_mv | Pädagogik Biologie Informatik |
doi_str_mv | 10.1017/9781108955652 |
format | Electronic eBook |
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illustrated | Not Illustrated |
index_date | 2024-07-03T17:33:57Z |
indexdate | 2024-07-10T09:09:24Z |
institution | BVB |
isbn | 9781108955652 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032741745 |
oclc_num | 1257811940 |
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owner_facet | DE-12 DE-92 DE-91 DE-BY-TUM DE-11 |
physical | 1 Online-Ressource (xiv, 371 Seiten) |
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publisher | Cambridge University Press |
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spelling | Baldi, Pierre 1957- (DE-588)105580482X aut Deep learning in science Pierre Baldi Cambridge Cambridge University Press 2021 1 Online-Ressource (xiv, 371 Seiten) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 22 Feb 2021) 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 Machine learning Science / Technological innovations Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Deep learning (DE-588)1135597375 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 s Maschinelles Lernen (DE-588)4193754-5 s Deep learning (DE-588)1135597375 s DE-604 Erscheint auch als Druck-Ausgabe 978-1-108-84535-9 https://doi.org/10.1017/9781108955652 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Baldi, Pierre 1957- Deep learning in science Machine learning Science / Technological innovations Neuronales Netz (DE-588)4226127-2 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Deep learning (DE-588)1135597375 gnd |
subject_GND | (DE-588)4226127-2 (DE-588)4193754-5 (DE-588)1135597375 |
title | Deep learning in science |
title_auth | Deep learning in science |
title_exact_search | Deep learning in science |
title_exact_search_txtP | Deep learning in science |
title_full | Deep learning in science Pierre Baldi |
title_fullStr | Deep learning in science Pierre Baldi |
title_full_unstemmed | Deep learning in science Pierre Baldi |
title_short | Deep learning in science |
title_sort | deep learning in science |
topic | Machine learning Science / Technological innovations Neuronales Netz (DE-588)4226127-2 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Deep learning (DE-588)1135597375 gnd |
topic_facet | Machine learning Science / Technological innovations Neuronales Netz Maschinelles Lernen Deep learning |
url | https://doi.org/10.1017/9781108955652 |
work_keys_str_mv | AT baldipierre deeplearninginscience |