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Inpher-Oracle Cloud Marketplace Partnership Offers Privacy Preserving Ai/Ml Platform
-Inpher-Oracle Cloud Marketplace Partnership…
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A Winning Go-to-Market Starts with Unification: From CMO to CRO
-In today’s hyper-competitive business…
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Flying Fuzzy: A Privacy Preserved No-Fly List for Global Airlines Using Fuzzy String Matching
-Author: Conor Moran (Senior…
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How to Build Machine Learning Models with Private Data Sources on AWS
-This article was originally published on AWS blogs by Conor Moran, Sr. Director, Business Development, Inpher.
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS Marketplace, enables data scientists to train and run machine learning models while maintaining data privacy and without trading utility. Data analysis and machine learning performed by XOR can improve model performance with mathematically guaranteed data privacy while ensuring the data never leaves the data source.
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Inpher’s Privacy-Preserving Cross-Border Analytics Case Study Published in Global FFIS Report
-LONDON, UK — As part of the technology working group on ‘The Role of Privacy Preserving Data Analytics in the…
Author archive for Marcella Arthur
Inpher > Articles by: Marcella Arthur