Privacy-preserving machine learning:
Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models. In Privacy Preserving Machine Learning, you will learn: Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthe...
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| Main Authors: | , , |
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| Format: | Book |
| Language: | English |
| Published: |
Shelter Island, NY
Manning Publications
[2023]
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| Subjects: | |
| Summary: | Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models. In Privacy Preserving Machine Learning, you will learn: Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthetic data generation Privacy-enhancing technologies for data mining and database applications Compressive privacy for machine learning 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 will benefit from incorporating these privacy-preserving practices into their model development. |
| Physical Description: | xx, 311 Seiten Illustrationen, Diagramme 24 cm |
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| 505 | 8 | |a Basics of privacy-preserving machine learning with differential privacy -- Local differential privacy and synthetic data generation -- Building privacy-assured machine learning applications | |
| 520 | |a Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models. In Privacy Preserving Machine Learning, you will learn: Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthetic data generation Privacy-enhancing technologies for data mining and database applications Compressive privacy for machine learning 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 will benefit from incorporating these privacy-preserving practices into their model development. | ||
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| 700 | 1 | |a Samaraweera, Dumindu |e Verfasser |4 aut | |
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Record in the Search Index
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| author | Chang, J. Morris Zhuang, Di Samaraweera, Dumindu |
| author_facet | Chang, J. Morris Zhuang, Di Samaraweera, Dumindu |
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| contents | Basics of privacy-preserving machine learning with differential privacy -- Local differential privacy and synthetic data generation -- Building privacy-assured machine learning applications |
| ctrlnum | (OCoLC)1389175688 (DE-599)BVBBV049027877 |
| discipline | Informatik |
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| id | DE-604.BV049027877 |
| illustrated | Illustrated |
| index_date | 2024-07-03T22:15:40Z |
| indexdate | 2024-07-10T09:53:12Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034290638 |
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| owner_facet | DE-1050 |
| physical | xx, 311 Seiten Illustrationen, Diagramme 24 cm |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Manning Publications |
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| spelling | Chang, J. Morris Verfasser aut Privacy-preserving machine learning J. Morris Chang, Di Zhuang, Dumindu Samaraweera Shelter Island, NY Manning Publications [2023] xx, 311 Seiten Illustrationen, Diagramme 24 cm txt rdacontent n rdamedia nc rdacarrier Basics of privacy-preserving machine learning with differential privacy -- Local differential privacy and synthetic data generation -- Building privacy-assured machine learning applications Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models. In Privacy Preserving Machine Learning, you will learn: Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthetic data generation Privacy-enhancing technologies for data mining and database applications Compressive privacy for machine learning 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 will benefit from incorporating these privacy-preserving practices into their model development. Machine learning Computer networks / Security measures Apprentissage automatique Réseaux d'ordinateurs / Sécurité / Mesures Computer networks / Security measures fast Machine learning fast Zhuang, Di Verfasser aut Samaraweera, Dumindu Verfasser aut |
| spellingShingle | Chang, J. Morris Zhuang, Di Samaraweera, Dumindu Privacy-preserving machine learning Basics of privacy-preserving machine learning with differential privacy -- Local differential privacy and synthetic data generation -- Building privacy-assured machine learning applications Machine learning Computer networks / Security measures Apprentissage automatique Réseaux d'ordinateurs / Sécurité / Mesures Computer networks / Security measures fast Machine learning fast |
| title | Privacy-preserving machine learning |
| title_auth | Privacy-preserving machine learning |
| title_exact_search | Privacy-preserving machine learning |
| title_exact_search_txtP | Privacy-preserving machine learning |
| title_full | Privacy-preserving machine learning J. Morris Chang, Di Zhuang, Dumindu Samaraweera |
| title_fullStr | Privacy-preserving machine learning J. Morris Chang, Di Zhuang, Dumindu Samaraweera |
| title_full_unstemmed | Privacy-preserving machine learning J. Morris Chang, Di Zhuang, Dumindu Samaraweera |
| title_short | Privacy-preserving machine learning |
| title_sort | privacy preserving machine learning |
| topic | Machine learning Computer networks / Security measures Apprentissage automatique Réseaux d'ordinateurs / Sécurité / Mesures Computer networks / Security measures fast Machine learning fast |
| topic_facet | Machine learning Computer networks / Security measures Apprentissage automatique Réseaux d'ordinateurs / Sécurité / Mesures |
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