Technical Debt in Machine Learning Systems (2015)

This article likely discusses the accumulation of technical debt in machine learning projects, a common issue where shortcuts and suboptimal solutions are adopted to expedite development, leading to future maintenance challenges and reduced system performance. The year 2015 suggests it's an early analysis of this problem.