A Survey of Zero-Knowledge Proof Based Verifiable Machine Learning

1. 1Understand the concept of zero-knowledge proofs and their application in machine learning
2. 2Identify the benefits of using ZKPs in verifiable machine learning, such as preserving data privacy and model confidentiality
3. 3Explore the different types of ZKPs and their suitability for various machine learning tasks
4. 4Investigate the current state of ZKP-based verifiable machine learning and its potential applications

Machine learning engineers and data scientists benefit from this survey as it provides a comprehensive overview of zero-knowledge proof based verifiable machine learning, enabling them to ensure the integrity and confidentiality of their models

💡 Zero-knowledge proofs provide a secure way to verify machine learning computations without revealing sensitive information

💡 Zero-knowledge proofs enable verifiable machine learning without compromising data privacy!