SeiyaKobayashi/zkml-optimization
Optimization for on-chain private machine learning.
This project helps machine learning developers deploy models that can make predictions using private user data while keeping that data confidential. It takes a trained machine learning model and enables it to generate verifiable, privacy-preserving predictions on sensitive inputs. The intended user is a machine learning developer working with private data on a blockchain.
No commits in the last 6 months.
Use this if you are a machine learning developer who needs to use a public model to make predictions on private user data on a blockchain without revealing the data itself.
Not ideal if you are looking for a general-purpose machine learning library or do not require on-chain, privacy-preserving predictions.
Stars
13
Forks
1
Language
TypeScript
License
MIT
Category
Last pushed
Oct 26, 2023
Commits (30d)
0
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