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Lessons Learned From Machine Learning Pipelines in Production
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- 1 Intro
- 2 Outline
- 3 1. Background: Machine learning in production
- 4 2. Assumption: Job specialization in machine learning projects
- 5 1-3. Issue for applying logics into production environment
- 6 1-4. Gaps between experimental and production environment
- 7 1-5. Challenges towards production environment
- 8 1-7. Overview of validation scenario and its target ML system
- 9 1. Utilizing Kedro to overcome challenges
- 10 3-1. Solution 1: Transforming pipelines in Kedro style
- 11 2-3-2. Step 1-A: Project Template Generation by Kedro
- 12 2-3-4. Step 1-C: Adding node not in notebook
- 13 2-3-6. Step 1-D: Connecting nodes to develop pipeline
- 14 2-5-2. Solution 3. Removing loop inside nodes extracted from Jupyter notebook
- 15 1. What we learned in validation scenario: good points
- 16 3. Possible solution
