The steaming link for the meetup: http://dai.ly/x4jzj7g
1. Project "Deep Water"- H2o's integration with Tensorflow by Jo-fai
This talk is about our recent project called "Deep Water". It is H2o's intergration with other deep learning libraries such as Tensorflow. I will go through the following topics: our motivation, potential benefits, H2o's interface and then a demo.
About Joe :https://uk.linkedin.com/in/jofaichow
Jo-fai (or Joe) is a data scientist at H2O.ai. Before joining H2O, he was in the business intelligence team at Virgin Media where he developed data products to enable quick and smart business decisions. He also worked (part-time) for Domino Data Lab 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 researcher 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.
2. Cracking crack mechanics—Using GANs and TensorFlow to replicate and learn more about fracture patterns by Julien Launay
When modeling transfers through a medium in civil engineering, knowing the precise influence of cracks is often complicated, doubly so since the transfer and fracture problems are often heavily linked. I will present a new way to generate “fake” cracking patterns using GANs, and will then expand on how such novel techniques can be used to learn more about fracture mechanics.
About Julien: https://fr.linkedin.com/in/julien-launay-400a7512a/en
Julien Launay is a civil servant student at Cachan’s École Normale Supérieure. He is pursuing a MSc in Civil Engineering, with a personal focus on machine learning. His research project aims at building TensorFlow based tools to study cracking patterns in concrete.