Privacy-Preserving Machine Learning : A use-case-driven approach to building and protecting ML pipelines from privacy and security threats

– 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 volume