Completed
1. Utilizing Kedro to overcome challenges
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Lessons Learned From Machine Learning Pipelines in Production
Automatically move to the next video in the Classroom when playback concludes
- 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
