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Machine Learning and Knowledge Extraction edited by Andreas Holzinger, Peter Kieseberg, Federico Cabitza, Andrea Campagner, A Min Tjoa, Edgar Weippl. [electronic resource] :

Contributor(s): Material type: TextTextPublication details: Cham Springer Nature Switzerland 2023Edition: 1st ed. 2023Description: XV, 320 p. 64 illus., 53 illus. in color. online resourceISBN:
  • 9783031408373
Subject(s): DDC classification:
  • 6.3
Online resources: Summary: 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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Item type Home library Call number Status Notes Date due Barcode Item holds
e-Book e-Book S. R. Ranganathan Learning Hub Online Available Platform:Springer EB2504
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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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