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Privacy-Preserving Machine Learning
Engelsk Paperback
Privacy-Preserving Machine Learning
Engelsk Paperback

601 kr
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Sikker betaling
6 - 8 hverdage

Om denne bog

Keep sensitive user data safe and secure, without sacrificing theaccuracy of your machine learning models.

In Privacy Preserving Machine Learning, you will learn:

  • Differential privacy techniques and their application insupervised learning
  • Privacy for frequency or mean estimation, Naive Bayes classifier,and deep learning
  • Designing and applying compressive privacy for machine learning
  • Privacy-preserving synthetic data generation approaches
  • Privacy-enhancing technologies for data mining and database applications

Privacy Preserving Machine Learning is a comprehensive guide to avoiding data breaches in your machine learning projects. You''ll get to grips with modern privacy-enhancing techniques such as differential privacy, compressive privacy, and synthetic data generation. Based on years of DARPA-funded cybersecurity research, ML engineers of all skill levels and seniorities will benefit from incorporating these privacy-preserving practices into their model development.

Product detaljer
Sprog:
Engelsk
Sider:
300
ISBN-13:
9781617298042
Indbinding:
Paperback
Udgave:
ISBN-10:
1617298042
Udg. Dato:
21 apr 2023
Længde:
21mm
Bredde:
236mm
Højde:
187mm
Forlag:
Manning Publications
Oplagsdato:
21 apr 2023
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