Paradigms of Applied Machine Learning: Systems Perspective | Dmitrii Kholodilov | MAANG
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.
What you'll learn from this talk:
• 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
🔗 Link to the event page
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