4th Annual Global Artificial Intelligence Conference - Webinar - Online Warm-Up (Free)

I will also discuss the common technical challenges of executing A/B tests on ML algorithms, such as infrastructure requirements, connecting online and offline metrics, and handling ramp up periods for online learning algorithms. Overall, the goal of this talk will be to motivate ML practitioners to use A/B testing when evaluating their algorithms and provide them with high-level guidelines on how to do it. Profile Pavel Dmitriev is a Vice President of Data Science at Outreach, where he works on enabling data driven decision making in sales through experimentation and machine learning. He was previously a Principal Data Scientist with Microsoft's Analysis and Experimentation team, where he worked on scaling experimentation in Bing, Skype, and Windows OS. Pavel co-authored numerous papers at top-tier data mining and machine learning conferences, such as WWW, ICSE, KDD, has given keynotes and tutorials at WWW, SIGIR, SEAA, and KDD.