Technical Debts in Machine Learning Projects and How to Mitigate Them

Explore the concept of technical debt in machine learning projects through this 30-minute conference talk by Maryna Karpusha, Machine Learning Research Team Lead at Borealis AI. Gain insights into the unique challenges ML systems face compared to classical software systems. Learn to identify various types of technical debts specific to ML projects and discover strategies for recognizing and mitigating these issues. Understand the importance of considering technical debt during system design to avoid costly future fixes. Delve into ML-specific risk factors that should be accounted for in system architecture, ensuring more robust and maintainable machine learning solutions.

Technical Debts in Machine Learning Projects and How to Mitigate Them