With global warming at its peak and fossil fuel reserves depleting swiftly, there is a worldwide need to switch to renewable energy sources and identify ways to expand the global energy reserves to meet the rising power demands.
Wind turbines have become a popular source of generating clean and renewable energy. Wind is an abundant and inexhaustible resource and one of the lowest-priced energy sources available today. The equipment needed can be designed to be effectively used in both agricultural and multi-use working landscapes.
Join us for a masterclass with our expert Christian H Ritter (Lead Data Scientist, Statistics Canada) to learn about how Machine Learning can be utilized to effectively predict the power output of a windmill based on various input features such as temperature, wind direction, turbine status, weather, blade length, and many other factors.
Agenda for the session
- How different parameters affect the Machine Learning model
- How to predict energy produced by a windmill
- Career opportunities unlocked through Artificial intelligence
- Q&A session with our expert
About Speakers
Christian Heiko Ritter
Lead Data Scientist, Stastics Canada
As an astrophysicist and passionate communicator, Christian H Ritter has over six years of experience in computer modeling and quantitative analysis. He has led international efforts to create a stellar database of TB-scale, built the first Python open-source galaxy code, and collaborated to get insight into the origin of elements through highly-parallelized 3D hydrodynamic simulations. He is passionate about communication, has delivered many international presentations, and promotes public speaking as the president of NiteShifters Toastmasters.
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