Name: Unlimited
Brand: Storytel
SKU: 7777
Availability: InStock

Srinivasa Rao Aravilli

– In an era of evolving privacy regulations, compliance is mandatory for every enterprise 

– Machine learning engineers face the dual challenge of analyzing vast amounts of data for insights while protecting sensitive information 

– This book addresses the complexities arising from large data volumes and the scarcity of in-depth privacy-preserving machine learning expertise, and covers a comprehensive range of topics from data privacy and machine learning privacy threats to real-world privacy-preserving cases 

– As you progress, you’ll be guided through developing anti-money laundering solutions using federated learning and differential privacy 

– Dedicated sections will explore data in-memory attacks and strategies for safeguarding data and ML models 

– You’ll also explore the imperative nature of confidential computation and privacy-preserving machine learning benchmarks, as well as frontier research in the field 

– Upon completion, you’ll possess a thorough understanding of privacy-preserving machine learning, equipping them to effectively shield data from real-world threats and attacks

Packt Publishing

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

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Storytel

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