Aravilli, S. R., & Hamilton, S. [ca. 2024]. Privacy-Preserving Machine Learning : A use-case-driven approach to building and protecting ML pipelines from privacy and security threats (1. Auflage) [Cd]. Birmingham: Packt Publishing Limited.
ISO-690 (author-date, English)ARAVILLI, Srinivasa Rao und HAMILTON, Sam, 2024. Privacy-Preserving Machine Learning : A use-case-driven approach to building and protecting ML pipelines from privacy and security threats. 1. Auflage. Birmingham: Packt Publishing Limited. ISBN 9781800564220.
Modern Language Association 9th editionAravilli, S. R., und S. Hamilton. Privacy-Preserving Machine Learning : A use-case-driven approach to building and protecting ML pipelines from privacy and security threats. 1. Auflage, cd, Packt Publishing Limited, 2024.
Mohr Siebeck - Recht (Deutsch - Österreich)Aravilli, Srinivasa Rao/Hamilton, Sam: Privacy-Preserving Machine Learning : A use-case-driven approach to building and protecting ML pipelines from privacy and security threats, 1. Auflage. Aufl. Birmingham 2024.
Emerald - HarvardAravilli, S.R. und Hamilton, S. (2024), Privacy-Preserving Machine Learning : A use-case-driven approach to building and protecting ML pipelines from privacy and security threats, 1. Auflage., Bd. , Packt Publishing Limited, Birmingham.