Data Science and Digital Systems: The 3Ds of Machine Learning Systems Design
This work addresses the problem of systematic ML system design for practitioners, but it appears incremental as it organizes existing concepts into a framework without introducing new methods.
The paper tackles the challenge of designing effective machine learning systems by proposing a framework centered on Data, Design, and Deployment (the 3Ds), aiming to shift towards a 'data first' approach in development.
Machine learning solutions, in particular those based on deep learning methods, form an underpinning of the current revolution in "artificial intelligence" that has dominated popular press headlines and is having a significant influence on the wider tech agenda. Here we give an overview of the 3Ds of ML systems design: Data, Design and Deployment. By considering the 3Ds we can move towards \emph{data first} design.