| 1. |
Buduma, Nikhil: Fundamentals of deep learning : designing next-generation machine intelligence algorithms / Nikhil Buduma ; with contributions by Nicholas Locascio.. - First edition.. -
Sebastopol, CA: O'Reilly Media, [2017]. - 1 online resource (1 volume) : illustrations
 Online-Ressource |
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| 2. |
Buduma, Nikhil: Fundamentals of deep learning : designing next-generation machine intelligence algorithms / Nikhil Buduma ; with contributions by Nicholas Locascio. - First edition. -
Beijing ; Boston ; Farnham ; Sebastopol ; Tokyo: O´Reilly, June 2017. - xii, 283 Seiten : Illustrationen, Diagramme, ISBN 978-1-4919-2561-4
 Buch/keine Angabe |
Signatur: LN-U 10-18611
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| 3. |
Buduma, Nikhil: Deep learning shen du xue xi ji chu : she ji xia yi dai ren gong zhi hui yan suan fa / Nikhil Buduma zhu ; Lan Zixuan yi. - [First edition].. -
[Place of publication not identified]: GoTop Information, Inc., [2018]. - 1 online resource (304 pages) : illustrationsDeep learning 深度學習基礎 : 設計下一代人工智慧演算法 / Nikhil Buduma 著 ; 藍子軒 譯.
Online-Ressource |
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| 4. |
Quantum computing and artificial intelligence : training machine and deep learning algorithms on quantum computers / edited by Pethuru Raj, Abhishek Kumar, Ashutosh Kumar Dubey, Surbhi Bhatia and Oswalt Manoj S. -
Berlin ; Boston: De Gruyter, [2023]. - XIII, 293 Seiten : Illustrationen, Diagramme, ISBN 978-3-11-079125-9
(Quantum Computing)
Buch/keine Angabe |
Signatur: LN-U 10-19883
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| 5. |
Federated learning systems : towards next-generation AI / Muhammad Habib ur Rehman, Mohamed Medhat Gaber (editors). -
Cham: Springer, [2021]. - 1 Online-Ressource (xvi, 196 Seiten) : Illustrationen, Diagramme, ISBN 978-3-030-70604-3
(Studies in computational intelligence ; volume 965)
Online-Ressource |
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| 6. |
Kouziokas, Georgios N.: Swarm intelligence and evolutionary computation : theory, advances and applications in machine learning and deep learning / Georgios N. Kouziokas, Lecturer, School of Engineering, University of Thessaly, Greece. - First edition. -
Boca Raton ; London ; New York: CRC Press, 2023. - 1 Online-Ressource (xiii, 203 Seiten) : Illustrationen, Diagramme, ISBN 978-1-003-24774-6
DOI: 10.1201/9781003247746
Online-Ressource |
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| 7. |
Kim, Hee Eun: Efficient deep learning at inference time for gram stained image classification / vorgelegt von Hee E. Kim ; Referent: Prof. Dr. med. Thomas Ganslandt. -
Heidelberg, 12 Jun. 2024. - 1 Online-Ressource (96 Seiten) : Illustrationen, Diagramme
DOI: 10.11588/heidok.00034902
Online-Ressource |
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| 8. |
Ketkar, Nikhil: Deep Learning with Python : Learn Best Practices of Deep Learning Models with PyTorch / Ketkar, Nikhil. - 2nd edition. -
[Erscheinungsort nicht ermittelbar]: Apress, 2021. - 1 online resource (316 pages), ISBN 978-1-4842-5364-9
Online-Ressource |
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| 9. |
Papa, Joe: PyTorch kompakt : Syntax, Design Patterns und Codebeispiele für Deep-Learning-Modelle / Joe Papa ; deutsche Übersetzung von Frank Langenau. - 1. Auflage. -
Heidelberg: O'Reilly, 2022. - 235 Seiten : Illustrationen, ISBN 978-3-96009-185-1
Buch/keine Angabe |
Signatur: LN-U 10-19621
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| 10. |
Iten, Raban: Artificial intelligence for scientific discoveries : extracting physical concepts from experimental data using deep learning / Raban Iten. -
Cham: Springer, 2023. - 1 Online-Ressource (XIII, 170 Seiten), ISBN 978-3-031-27019-2
DOI: 10.1007/978-3-031-27019-2
Online-Ressource |
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| 11. |
Konopczynski, Tomasz: Deep learning segmentation algorithms for X-ray CT data / put forward by Master of scienceTomasz Kazimierz Konopczynski ; advisors: Prof. Dr. Jürgen Hesser [u… . -
Heidelberg, 19 Jul. 2021. - 1 Online-Ressource (107 Seiten) : Illustrationen, Diagramme
DOI: 10.11588/heidok.00030239
Online-Ressource |
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| 12. |
Ayala, Leonardo: Translational functional imaging in surgery enabled by deep learning / vorgelegt von Leonardo Antonio Ayala Menjivar ; Doktormutter: Lena Maier-Hein. -
Heidelberg, 17 Jul. 2023. - 1 Online-Ressource (204 Seiten) : Illustrationen, Diagramme
DOI: 10.11588/heidok.00033281
Online-Ressource |
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| 13. |
Wang, Chi: Designing deep learning systems : a guide for software engineers / Chi Wang and Donald Szeto ; code lab by Yan Xue ; foreword by Silvio Savarese and Caiming Xiong. -
Shelter Island, NY: Manning, [2023]. - xx, 337 Seiten : Illustrationen, Diagramme, ISBN 978-1-63343-986-3
Buch/keine Angabe |
Signatur: LN-U 10-19881
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| 14. |
Golla, Alena-Kathrin: Optimized training pipeline for deep learning applications in medical image processing / vorgelegt von Alena-Kathrin Golla ; Referent: Prof. Dr. Ing. Frank G. Zöllner. -
Heidelberg, 2022. - 1 Online-Ressource (xviii, 112 Seiten) : Illustrationen, Diagramme
DOI: 10.11588/heidok.00030833
Online-Ressource |
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| 15. |
Kim, Hee Eun: Efficient deep learning at inference time for gram stained image classification / vorgelegt von Hee E. Kim ; Referent: Prof. Dr. med. Thomas Ganslandt. -
Heidelberg, [2024?]. - 84 Seiten : Illustrationen, Diagramme
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| 16. |
Buduma, Nikhil: 実践 Deep Learning ―PythonとTensorFlowで学ぶ次世代の機械学習アルゴリズム / Buduma, Nikhil. - 1st edition. -
[Erscheinungsort nicht ermittelbar]: O'Reilly Japan, Inc., 2018. - 1 online resource (336 pages), ISBN 978-4-87311-832-1
Online-Ressource |
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| 17. |
Hirschle, Jochen: Machine Learning für Zeitreihen : Einstieg in Regressions-, ARIMA- und Deep-Learning-Verfahren mit Python / Jochen Hirschle. -
München: Hanser, [2021]. - VII, 267 Seiten : Illustrationen, Diagramme, ISBN 978-3-446-46726-2
Buch/keine Angabe  Inhaltsverzeichnis: 1, 2 |
Signatur: LN-U 10-19463
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| 18. |
Aggarwal, Charu C.: Neural Networks and Deep Learning : A Textbook / by Charu C. Aggarwal. - 2nd ed. 2023.. -
Cham: Springer International Publishing, 2023.. - 1 Online-Ressource(XXIV, 529 p. 150 illus., 22 illus. in color.), ISBN 978-3-031-29642-0
DOI: 10.1007/978-3-031-29642-0
Online-Ressource |
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| 19. |
Rothman, Denis: Transformers for natural language processing : build, train, and fine-tuning deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, and GPT-3 / Denis Rothman ; foreword by Antonio Gulli. - Second edition.. -
[Birmingham, United Kingdom]: Packt Publishing, [2022]. - 1 online resource (564 pages) : illustrations, ISBN 978-1-80324-733-5
(Expert insight)
Online-Ressource |
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| 20. |
Mihaylov, Todor: Knowledge-enhanced neural networks for machine reading comprehension / Todor Borisov Mihaylov ; supervisor: Prof. Dr. Anette Frank. -
Heidelberg, 2022. - 1 Online-Ressource (ix, 159 Seiten)
DOI: 10.11588/heidok.00034352
Online-Ressource |
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