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100%: Katharine Jarmul: Practical Data Privacy (ISBN: 9781098129439) O'Reilly Media, in Englisch, auch als eBook.Nur diese Ausgabe anzeigen…
100%: Katharine Jarmul: Practical Data Privacy (ISBN: 9781098129422) in Englisch, auch als eBook.Nur diese Ausgabe anzeigen…
Practical Data Privacy - 3 Angebote vergleichen
Bester Preis: € 37,24 (vom 01.05.2023)1
Practical Data Privacy
EN NW EB DLISBN: 9781098129439 bzw. 1098129431, in Englisch, O'Reilly Media, neu, E-Book, elektronischer Download.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, Despatched same working day before 3pm.
Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems.Practical Data Privacy answers important questions such as:What do privacy regulations like GDPR and CCPA mean for my data workflows and data science use cases?What does "anonymized data" really mean? How do I actually anonymize data?How does federated learning and analysis work?Homomorphic encryption sounds great, but is it ready for use?How do I compare and choose the best privacy-preserving technologies and methods? Are there open-source libraries that can help?How do I ensure that my data science projects are secure by default and private by design?How do I work with governance and infosec teams to implement internal policies appropriately?
Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems.Practical Data Privacy answers important questions such as:What do privacy regulations like GDPR and CCPA mean for my data workflows and data science use cases?What does "anonymized data" really mean? How do I actually anonymize data?How does federated learning and analysis work?Homomorphic encryption sounds great, but is it ready for use?How do I compare and choose the best privacy-preserving technologies and methods? Are there open-source libraries that can help?How do I ensure that my data science projects are secure by default and private by design?How do I work with governance and infosec teams to implement internal policies appropriately?
2
Practical Data Privacy
EN NW EB DLISBN: 9781098129422 bzw. 1098129423, in Englisch, O'Reilly Media, neu, E-Book, elektronischer Download.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, Despatched same working day before 3pm.
Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems.Practical Data Privacy answers important questions such as:What do privacy regulations like GDPR and CCPA mean for my data workflows and data science use cases?What does "anonymized data" really mean? How do I actually anonymize data?How does federated learning and analysis work?Homomorphic encryption sounds great, but is it ready for use?How do I compare and choose the best privacy-preserving technologies and methods? Are there open-source libraries that can help?How do I ensure that my data science projects are secure by default and private by design?How do I work with governance and infosec teams to implement internal policies appropriately?
Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems.Practical Data Privacy answers important questions such as:What do privacy regulations like GDPR and CCPA mean for my data workflows and data science use cases?What does "anonymized data" really mean? How do I actually anonymize data?How does federated learning and analysis work?Homomorphic encryption sounds great, but is it ready for use?How do I compare and choose the best privacy-preserving technologies and methods? Are there open-source libraries that can help?How do I ensure that my data science projects are secure by default and private by design?How do I work with governance and infosec teams to implement internal policies appropriately?
3
Practical Data Privacy
ENISBN: 9781098129422 bzw. 1098129423, in Englisch, Vitalsource Technologies, Inc.
Lieferung aus: Vereinigte Staaten von Amerika, Lagernd.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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