Privacy-Preserving Machine Learning: A use-case-driven approach to building and protecting ML pipelines from privacy and security threats

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TextPublication details: Birmingham: Packt Publishing, 2023Edition: 1st EdiDescription: 402pISBN:

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Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Book	Air University Multan Campus Library Computer Science		Computer Science		006.31 ARA-P (Browse shelf(Opens below))					Available			P005251

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Previous	006.3 MOH-D Deep Learning-Powered Technologies: autonomous driving, Artificial Intelligence of things (AIoT), augmented reality, 5G Communications and beyond	006.3 PAU-E Embedding Knowledge Graphs with RDF2vec	006.31 ABO-M Machine Learning in Microservices: Productionizing microservices architecture for machine learning solutions	006.31 ARA-P Privacy-Preserving Machine Learning: A use-case-driven approach to building and protecting ML pipelines from privacy and security threats	006.31 BAL-C Conformal Prediction for Reliable Machine Learning: theory, adaptations and applications	006.31 HOA-D Deep Reinforcement Learning for Wireless Communications and Networking: theory, applications and implementation	006.31 LAN-M Machine Learning with R: Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data	Next

Includes Index.

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