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Privacy-Preserving Machine Learning - ebook
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Privacy-Preserving Machine Learning - ebook
– 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
| Kategoria: | Technology |
| Język: | Angielski |
| Zabezpieczenie: |
Watermark
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| ISBN: | 978-1-80056-422-0 |
| Rozmiar pliku: | 10 MB |
