Decentralized Machine Learning (DML) protocol is designed to expand the reach to untapped private data and unleash their potential to facilitate machine learning development while providing economic incentives and protecting data privacy. Machine learning algorithm will be run on the devices without extracting the data from the devices, which will be kept within the devices. Only the machine learning result will be aggregated with outcomes generated from other devices to form an unbiased, comprehensive and accurate crowdsourced analytics and predictions. Through DML protocol, both the private data and processing power for machine learning are decentralized as algorithms are run directly on individual devices by utilizing their idle processing power.