Building Continuous Integration Services for Machine Learning

28Citations
Citations of this article
83Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Continuous integration (CI) has been a de facto standard for building industrial-strength software. Yet, there is little attention towards applying CI to the development of machine learning (ML) applications until the very recent effort on the theoretical side. In this paper, we take a step forward to bring the theory into practice. We develop the first CI system for ML, to the best of our knowledge, that integrates seamlessly with existing ML development tools. We present its design and implementation details.

Cite

CITATION STYLE

APA

Karlaš, B., Interlandi, M., Renggli, C., Wu, W., Zhang, C., Mukunthu Iyappan Babu, D., … Weimer, M. (2020). Building Continuous Integration Services for Machine Learning. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 2407–2415). Association for Computing Machinery. https://doi.org/10.1145/3394486.3403290

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free