In this hands-on workshop, we'll demystify Zero Knowledge Proofs (ZKP) and their practical applications in machine learning by building a real-world application from scratch. Drawing from experience developing ZK applications at Nethermind and various blockchain projects, we'll demonstrate how to create privacy-preserving ML solutions that can be immediately implemented in production environments.
The workshop will guide participants through:

Building a simple ML model with privacy guarantees using ZK circuits
Implementing efficient proof generation for ML inference
Deploying and integrating with Ethereum smart contracts
Practical optimization techniques for production use

Using popular tools like Circom and Solidity, we'll create a working prototype that attendees can use as a foundation for their own projects. This session bridges the gap between theoretical ZK concepts and practical implementation, making it valuable for developers and technical decision-makers looking to integrate privacy-preserving ML solutions into their blockchain applications.