Welcome to the Swiss Big Data User Group - Switzerland's biggest Big Data community. The group aims to bring together people from all industries who are interested in dealing with large amounts of data, to offer interesting talks, hands-on advice and a forum for exchange and networking.
We are thrilled to finally announce the next SBDUG-Meetup!
PLEASE NOTE: The agenda details are still subject to change as we are awaiting confirmation by further speakers.
Location sponsored by Scigility:
Europaallee 41, Zurich (1st Floor – follow the SBDUG signs leading the way)
Agenda (subject to change as we are awaiting confirmation by further speakers):
- 17:30 Networking & Apéro
- 18:30 Talk 1: Reinforcement Learning: a gentle introduction and industrial application (Dr. Christian Hidber)
Details Talk 1:
Reinforcement Learning: a gentle introduction and industrial application
Reinforcement learning learns complex processes autonomously. No big data sets with the "right" answers are needed; the algorithms learn by experimenting. By using reinforcement learning, robots learn to walk, beat the world champion in Go, or fly a helicopter.
This talk shows "how" and "why" reinforcement learning algorithms work in an intuitive fashion, illustrating their inner-workings by the way a child learns to play a new game. We show what it takes to rephrase a real world problem as a reinforcement learning task and take a look at the challenges to bring it into production on 7000 client in 42 countries all around the world.
Our industrial application is based on siphonic roof drainage systems. It warrants that large buildings like stadiums, airports, or shopping malls do not collapse during heavy rainfalls. Choosing the "right" diameters is difficult, requiring intuition and hydraulic expertise. As of today, no feasible, deterministic algorithm is known. Using reinforcement learning we were able to reduce the fail rate of our existing solution – based on classic supervised learning – by more than 70%.
Dr. Christian Hidber is a consultant at bSquare with a focus on Machine Learning, .Net development, and Azure, and an international conference speaker. He has a PhD in computer algebra from ETH Zurich and did a postdoc at UC Berkeley where he researched online data mining algorithms. Currently, he applies machine learning to industrial hydraulics simulations.