ChainML is intended to bridge the gap between popular machine learning frameworks (PyTorch, sklearn, JAX, TensorFlow) and Web3 technologies, enabling the development, training, and deployment of machine learning models in a decentralized environment.
The primary objective of ChainML is to facilitate seamless integration of machine learning operations with blockchain technologies, smart contracts, and decentralized applications (DApps), promoting privacy, security, and data ownership.
• ChainML is designed to integrate common machine learning frameworks Web3 technologies, facilitating model development, training, and deployment in decentralized environments.
• The package will be compatible with leading blockchain networks supporting the deployment and interaction with smart contracts for executing machine learning tasks.
• The plan includes engaging with the developer and data science communities for feedback, aiming for continuous improvement, and addressing the evolving needs of decentralized machine learning applications.
