pse.dev/content/projects/zkml.md

id, name, image, section, projectStatus, category, tldr, tags, links

id	name	image	section	projectStatus	category	tldr	tags	links
zkml	ZKML	zkml.webp	pse	inactive	research	ZKML (Zero-Knowledge Machine Learning) leverages zero-knowledge proofs for privacy-preserving machine learning, enabling model and data privacy with transparent verification.	keywords themes types builtWith Anonymity/privacy Scaling research Proof of concept Infrastructure/protocol circom halo2 nova	github https://github.com/socathie/circomlib-ml

ZKML is a solution that combines the power of zero-knowledge proofs (ZKPs) and machine learning to address the privacy concerns in traditional machine learning. It provides a platform for machine learning developers to convert their TensorFlow Keras models into ZK-compatible versions, ensuring model privacy, data privacy, and transparent verification. ZKML can be used to verify if a specific machine learning model was used to generate a particular piece of content, without revealing the input or the model used. It has potential use cases in on-chain biometric authentication, private data marketplace, proprietary ML model sharing, and AIGC NFTs.