Deep Water is H2O’s integration with multiple open source deep learning libraries such as TensorFlow, MXNet and Caffe. On top of the performance gains from GPU backends, Deep Water naturally inherits all H2O properties in scalability. ease of use and deployment. In his talk, Jo-fai will go through the motivation and benefits of Deep Water. Finishing with a demonstration of how to build and deploy deep learning models with or without programming experience using H2O’s R/Python/Flow (Web) interfaces.
Data Scientist, H2O.ai
Jo-fai (or Joe) is a data scientist at H2O.ai. Before joining H2O, he was in the business intelligence team at Virgin Media in UK where he developed data products to enable quick and smart business decisions. He also worked remotely for Domino Data Lab in US as a data science evangelist promoting products via blogging and giving talks at meetups. Joe has a background in water engineering. Before his data science journey, he was an EngD research engineer at STREAM Industrial Doctorate Centre working on machine learning techniques for drainage design optimization. Prior to that, he was an asset management consultant specialized in data mining and constrained optimization for the utilities sector in UK and abroad. He also holds a MSc in Environmental Management and a BEng in Civil Engineering.