Machine Learning and Knowledge Extraction edited by Andreas Holzinger, Peter Kieseberg, Federico Cabitza, Andrea Campagner, A Min Tjoa, Edgar Weippl. [electronic resource] :
Material type: TextPublication details: Cham Springer Nature Switzerland 2023Edition: 1st ed. 2023Description: XV, 320 p. 64 illus., 53 illus. in color. online resourceISBN:- 9783031408373
- Artificial intelligence
- Artificial Intelligence
- Data Mining and Knowledge Discovery
- Data mining
- Database management
- Database Management
- Formal Languages and Automata Theory
- Information storage and retrieval systems
- Information Storage and Retrieval
- Machine theory
- Software engineering
- Software Engineering
- 6.3
Item type | Home library | Call number | Status | Notes | Date due | Barcode | Item holds | |
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e-Book | S. R. Ranganathan Learning Hub Online | Available | Platform:Springer | EB2504 |
This volume LNCS-IFIP constitutes the refereed proceedings of the 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2023 in Benevento, Italy, during August 28 - September 1, 2023. The 18 full papers presented together were carefully reviewed and selected from 30 submissions. The conference focuses on integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.
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