Felix Wick - ML Based Time Series Regression| PyData Global 2020

Talk By using demand forecasting as example, I will introduce various crucial concepts for making time series predictions with machine learning models, ranging from feature engineering and preprocessing to explainable and causal ML. Speaker Felix Wick received his PhD in high energy physics at the Karlsruhe Institute of Technology in 2011. For several years, he then led the machine learning team at Blue Yonder, a provider of cloud-based predictive applications focussing on the retail market, and developed new methods for demand forecasting and causal inference. After acquisition of Blue Yonder by JDA, a leading provider of supply chain management software, and subsequent re-branding of the merged company to Blue Yonder, he now runs the data science and machine learning R&D organization, and strives for construction of an autonomous supply chain powered by artificial intelligence. www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps