Shypd.aiThe largest open index of AI toolstf-encrypted is an open-source framework for encrypted machine learning in TensorFlow. It enables training and prediction over encrypted data using secure multi-party computation and homomorphic encryption, making privacy-preserving ML accessible.
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tf-encrypted is an open-source framework designed to bring privacy-preserving machine learning to TensorFlow. It allows developers to perform training and prediction on encrypted data by leveraging secure multi-party computation and homomorphic encryption. The framework aims to simplify privacy-preserving ML, removing the need for deep expertise in cryptography, distributed systems, or high-performance computing. It integrates with TensorFlow 2, supporting eager execution for easier development, and also allows for implicit graph building with `tfe.function` to maintain performance. tf-encrypted provides examples and documentation to help users get started with secure matrix multiplication, neural network inference, and training on encrypted data, showcasing its capabilities with benchmarks for various models and protocols.
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