About the talk
This talk delves into several paradigms of applied machine learning, examining how different approaches are employed to solve business problems across diverse industries. We will explore the technical constraints and system design approaches that drive the evolution of these techniques.
This talk will cover
- Risk modeling and forecasting problems in traditional enterprises, showcasing how machine learning aids in decision-making and risk mitigation
- Modern approach to personalized recommendations used by internet companies, highlighting the advanced algorithms that provide tailored content to users and systems that power such recommendations
- The emerging field of self-supervised and generative AI, discussing the untapped opportunities it offers for businesses and its unique technical considerations
Web Development
About the speaker
Engineering leader with background in distributed systems, data analytics and machine learning. Building ML/AI-powered systems since 2012, with experience spanning across traditional industries (banking, telecom, retail) and internet companies.