참고문헌
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- AltexSoft, "What is data engineering: Explaining the data pipeline, data warehouse, and data engineer role," June 2019, https://www.altexsoft.com/blog/datascience/what-is-dataengineering-explaining-data-pipeline-data-warehouse-anddata-engineer-role/
- 정창헌, "Data warehouse vs. data lake," 2017. 7. 12. https://blog.b2en.com/253
- J. Dowling, "Feature store vs data warehouse," Oct. 10, 2020, https://medium.com/data-for-ai/feature-store-vs-datawarehouse-306d1567c100
- J. K. Park and H. S. Hwang, "Feature store란?," Sept. 24, 2020, https://medium.com/daria-blog/feature-store-%EB%9E%80-4c53d18c1149
- http://featurestore.org/
- A. Holler and M. Mui, "Evolving michelangelo model representation for flexibility at scale," Oct. 16, 2019, https://eng.uber.com/michelangelo-machine-learning-modelrepresentation/
- J. Hermann and M. Del Balso, "Meet michelangelo: Uber's machine learning platform," Sept. 5, 2017, https://eng.uber.com/michelangelo/
- M. Del Balso, "Tecton: The data platform for machine learning" Apr. 28, 2020, https://www.tecton.ai/blog/data-platform-ml/
- https://github.com/logicalclocks/hopsworks
- A. A. Ormenis et al., "Horizontally scalable ml pipelines with a feature store," Mar. 20, 2019, https://mlsys.org/Conferences/2019/doc/2019/demo_7.pdf
- https://hopsworks.readthedocs.io/en/latest/featurestore/guides/featurestore.html
- https://github.com/feast-dev/feast
- Feast, "What is feast," https://docs.feast.dev/