Deep learning, reinforcement learning, and the rise of intelligent systems:
The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansio...
Gespeichert in:
| Weitere Verfasser: | , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey PA, USA
IGI Global
[2024]
|
| Schriftenreihe: | Advances in computational intelligence and robotics (ACIR) book series
|
| Schlagworte: | |
| Online-Zugang: | DE-91 DE-898 Volltext |
| Zusammenfassung: | The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields.Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals. |
| Beschreibung: | 1 Online-Ressource (xvi, 291 Seiten) Illustrationen |
| ISBN: | 9798369317396 |
| DOI: | 10.4018/979-8-3693-1738-9 |
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| id | DE-604.BV049645338 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:39:47Z |
| indexdate | 2024-08-24T01:06:59Z |
| institution | BVB |
| isbn | 9798369317396 |
| language | English |
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| physical | 1 Online-Ressource (xvi, 291 Seiten) Illustrationen |
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| publisher | IGI Global |
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| series2 | Advances in computational intelligence and robotics (ACIR) book series |
| spelling | Deep learning, reinforcement learning, and the rise of intelligent systems M. Irfan Uddin, Wali Khan Mashwani Hershey PA, USA IGI Global [2024] © 2024 1 Online-Ressource (xvi, 291 Seiten) Illustrationen txt rdacontent c rdamedia cr rdacarrier Advances in computational intelligence and robotics (ACIR) book series The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields.Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals. Deep learning (Machine learning) Industrial applications Uddin, M. Irfan 1982- edt Mashwani, Wali Khan 1972- edt Erscheint auch als Druck-Ausgabe 979-8-3693-1738-9 Erscheint auch als Druck-Ausgabe, Paperback 979-8-3693-4568-9 https://doi.org/10.4018/979-8-3693-1738-9 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Deep learning, reinforcement learning, and the rise of intelligent systems Deep learning (Machine learning) Industrial applications |
| title | Deep learning, reinforcement learning, and the rise of intelligent systems |
| title_auth | Deep learning, reinforcement learning, and the rise of intelligent systems |
| title_exact_search | Deep learning, reinforcement learning, and the rise of intelligent systems |
| title_exact_search_txtP | Deep learning, reinforcement learning, and the rise of intelligent systems |
| title_full | Deep learning, reinforcement learning, and the rise of intelligent systems M. Irfan Uddin, Wali Khan Mashwani |
| title_fullStr | Deep learning, reinforcement learning, and the rise of intelligent systems M. Irfan Uddin, Wali Khan Mashwani |
| title_full_unstemmed | Deep learning, reinforcement learning, and the rise of intelligent systems M. Irfan Uddin, Wali Khan Mashwani |
| title_short | Deep learning, reinforcement learning, and the rise of intelligent systems |
| title_sort | deep learning reinforcement learning and the rise of intelligent systems |
| topic | Deep learning (Machine learning) Industrial applications |
| topic_facet | Deep learning (Machine learning) Industrial applications |
| url | https://doi.org/10.4018/979-8-3693-1738-9 |
| work_keys_str_mv | AT uddinmirfan deeplearningreinforcementlearningandtheriseofintelligentsystems AT mashwaniwalikhan deeplearningreinforcementlearningandtheriseofintelligentsystems |