  Previous machine learning (ML) system development research suggests that
emerging software quality attributes are a concern due to the probabilistic
behavior of ML systems. Assuming that detailed development processes depend on
individual developers and are not discussed in detail. To help developers to
standardize their ML system development processes, we conduct a preliminary
systematic literature review on ML system development processes. A search query
of 2358 papers identified 7 papers as well as two other papers determined in an
ad-hoc review. Our findings include emphasized phases in ML system
developments, frequently described practices and tailored traditional software
development practices.
