Technical Debt In Machine Learning System - A Model Driven Perspective - DataScienceCentral.com

This article is part 2 of the two part series on Technical Debt in Machine Learning Systems development. Introduced a simple yet powerful Model of Technical Debt for Machine Learning Systems. The model is simple to remember, easier to extend, and provides a reliable means for reliable and maintainable Machine Learning Systems. This, in a nutshell, is the value proposition of this post. Introduced four dimensions of the Model, namely, Time, Input, System and Output.