  As machine learning is applied more widely, it is necessary to have a machine
learning platform for both infrastructure administrators and users including
expert data scientists and citizen data scientists to improve their
productivity. However, existing machine learning platforms are ill-equipped to
address the "Machine Learning tech debts" such as glue code, reproducibility,
and portability. Furthermore, existing platforms only take expert data
scientists into consideration, and thus they are inflexible for infrastructure
administrators and non-user-friendly for citizen data scientists. We propose
Submarine, a unified machine learning platform, to address the challenges.
