Architecting AI Deployment: A Systematic Review of State-of-the-Art and State-of-Practice Literature-Reference-Cited by-同舟云学术

Architecting AI Deployment: A Systematic Review of State-of-the-Art and State-of-Practice Literature

Published:2021 Issue: Volume: Page:14-29
ISSN:1865-1348
Container-title:Lecture Notes in Business Information Processing
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Author:

John Meenu Mary,Holmström Olsson Helena,Bosch Jan

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-67292-8_2

Reference38 articles.

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2. Bernardi, L., Mavridis, T., Estevez, P.: 150 successful machine learning models: 6 lessons learned at booking. com. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1743–1751, July 2019

3. Sculley, D., et al.: Hidden technical debt in machine learning systems. In: Advances in Neural Information Processing Systems, pp. 2503–2511 (2015)

4. Dahlmeier, D.: On the challenges of translating NLP research into commercial products. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 92–96, July 2017

5. Crankshaw, D., Gonzalez, J., Bailis, P.: Research for practice: prediction-serving systems. Commun. ACM 61(8), 45–49 (2018)

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