1. Intro to H2O & IoT Use Cases
Intro to H2O & IoT Use Cases: In this talk, I will give you an overview of our company (H2O.ai), our open-source machine learning platform (H2O) as well as our new projects (e.g. Deep Water and Steam). This will be useful for attendees who are not familiar with H2O. After the introduction, I will show you how to use H2O for two common IoT use cases: predictive maintenance and anomaly detection.
2. Deep Water - Making Deep Learning Accessible to Everyone
Deep Water: 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 this
talk, Joe will go through the motivation and benefits of Deep Water.
After that, he will demonstrate how to build and deploy deep learning
models with or without programming experience using H2O's R/Python/Flow
BIO Jo-fai (or Joe) Chow 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 the 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 the UK and abroad. He also holds an MSc in Environmental Management and a BEng in Civil Engineering. LinkedIn - https://www.linkedin.com/in/jofaichow/
Dr. Maciej Beręsewicz