Advancing software engineering through AI, federated learning, and large language models:
Advancing software engineering through AI, federated learning, and large language models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. It equips readers with the knowledge and practical insights needed to harn...
Gespeichert in:
Hauptverfasser: | , , , , |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Hershey PA, USA
IGI Global
[2024]
|
Schriftenreihe: | Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series
|
Schlagworte: | |
Online-Zugang: | DE-91 DE-898 DE-1050 Volltext |
Zusammenfassung: | Advancing software engineering through AI, federated learning, and large language models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. It equips readers with the knowledge and practical insights needed to harness these technologies effectively, enhancing software development, testing, maintenance, and deployment processes. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. |
Beschreibung: | 1 Online-Ressource (xxi, 354 Seiten) Illustrationen |
ISBN: | 9798369335031 |
DOI: | 10.4018/979-8-3693-3502-4 |
Internformat
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700 | 1 | |a Chanderwal, Nitin |d 1978- |e Verfasser |4 aut | |
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Datensatz im Suchindex
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author | Sharma, Avinash Kumar 1982- Chanderwal, Nitin 1978- Prajapati, Amarjeet Singh, Pancham Kansal, Mrignainy |
author_facet | Sharma, Avinash Kumar 1982- Chanderwal, Nitin 1978- Prajapati, Amarjeet Singh, Pancham Kansal, Mrignainy |
author_role | aut aut aut aut aut |
author_sort | Sharma, Avinash Kumar 1982- |
author_variant | a k s ak aks n c nc a p ap p s ps m k mk |
building | Verbundindex |
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dewey-full | 005.1028 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 005 - Computer programming, programs, data, security |
dewey-raw | 005.1028 |
dewey-search | 005.1028 |
dewey-sort | 15.1028 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
doi_str_mv | 10.4018/979-8-3693-3502-4 |
format | Electronic eBook |
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id | DE-604.BV049735972 |
illustrated | Illustrated |
indexdate | 2024-12-17T19:01:34Z |
institution | BVB |
isbn | 9798369335031 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035078079 |
oclc_num | 1443579678 |
open_access_boolean | |
owner | DE-91 DE-BY-TUM DE-898 DE-BY-UBR DE-1050 |
owner_facet | DE-91 DE-BY-TUM DE-898 DE-BY-UBR DE-1050 |
physical | 1 Online-Ressource (xxi, 354 Seiten) Illustrationen |
psigel | ZDB-98-IGB ZDB-98-IGB TUM_Paketkauf_2024 ZDB-98-IGB FHR_PDA_IGB |
publishDate | 2024 |
publishDateSearch | 2024 |
publishDateSort | 2024 |
publisher | IGI Global |
record_format | marc |
series2 | Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series |
spelling | Sharma, Avinash Kumar 1982- Verfasser aut Advancing software engineering through AI, federated learning, and large language models Avinash Kumar Sharma, Nitin Chanderwal, Amarjeet Prajapati, Pancham Singh, Mrignainy Kansal Advancing software engineering through artificial intelligence, federated learning, and large language models Hershey PA, USA IGI Global [2024] © 2024 1 Online-Ressource (xxi, 354 Seiten) Illustrationen txt rdacontent c rdamedia cr rdacarrier Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series Advancing software engineering through AI, federated learning, and large language models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. It equips readers with the knowledge and practical insights needed to harness these technologies effectively, enhancing software development, testing, maintenance, and deployment processes. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Software engineering Chanderwal, Nitin 1978- Verfasser aut Prajapati, Amarjeet Verfasser aut Singh, Pancham Verfasser aut Kansal, Mrignainy Verfasser aut Erscheint auch als Druck-Ausgabe, Paperback 979-8-3693-4875-8 Erscheint auch als Druck-Ausgabe, Hardcover 979-8-3693-3502-4 https://doi.org/10.4018/979-8-3693-3502-4 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Sharma, Avinash Kumar 1982- Chanderwal, Nitin 1978- Prajapati, Amarjeet Singh, Pancham Kansal, Mrignainy Advancing software engineering through AI, federated learning, and large language models Software engineering |
title | Advancing software engineering through AI, federated learning, and large language models |
title_alt | Advancing software engineering through artificial intelligence, federated learning, and large language models |
title_auth | Advancing software engineering through AI, federated learning, and large language models |
title_exact_search | Advancing software engineering through AI, federated learning, and large language models |
title_full | Advancing software engineering through AI, federated learning, and large language models Avinash Kumar Sharma, Nitin Chanderwal, Amarjeet Prajapati, Pancham Singh, Mrignainy Kansal |
title_fullStr | Advancing software engineering through AI, federated learning, and large language models Avinash Kumar Sharma, Nitin Chanderwal, Amarjeet Prajapati, Pancham Singh, Mrignainy Kansal |
title_full_unstemmed | Advancing software engineering through AI, federated learning, and large language models Avinash Kumar Sharma, Nitin Chanderwal, Amarjeet Prajapati, Pancham Singh, Mrignainy Kansal |
title_short | Advancing software engineering through AI, federated learning, and large language models |
title_sort | advancing software engineering through ai federated learning and large language models |
topic | Software engineering |
topic_facet | Software engineering |
url | https://doi.org/10.4018/979-8-3693-3502-4 |
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