Amazing tutorial, thanks! I've got two questions. 1. @6:40 what are CreateClusterOp, AnalyzeOp, etc... ? 2. @12:28 "each components are individual docker" but aren't sum1(a+b), sum2(c+d), sum3 (sum1 + sum3) inside one python function in @dsl.pipeline generator? if not, @10:47 is creating 3 components instead of one which perform three addition?
After creating a pipeline can we test it with different parameters w/o creating a new pipeline? for ex: @10:33 you've specified a,b,c,d but I'm wondering if I can try different a,b,c,d with one pipeline.
The "Experiement" funtionality is exactly what serves this purpose. You can run multiple iterations with different parameters under one Experiment ID. Also you may select what metrics needs to be tracked in each of the iteration.
This is the very good starting point to learn kubeflow
The best introduction to the kfp!
Amazing tutorial, thanks! I've got two questions.
1. @6:40 what are CreateClusterOp, AnalyzeOp, etc... ?
2. @12:28 "each components are individual docker" but aren't sum1(a+b), sum2(c+d), sum3 (sum1 + sum3) inside one python function in @dsl.pipeline generator? if not, @10:47 is creating 3 components instead of one which perform three addition?
but how to install kubeflow on aws, i tried, we dont have any good tutorial on internet!
did u got answer,
After creating a pipeline can we test it with different parameters w/o creating a new pipeline? for ex: @10:33 you've specified a,b,c,d but I'm wondering if I can try different a,b,c,d with one pipeline.
The "Experiement" funtionality is exactly what serves this purpose. You can run multiple iterations with different parameters under one Experiment ID. Also you may select what metrics needs to be tracked in each of the iteration.
Appreciate if we can get access to the jupyter notebook you using here.. Thnks
29:46
a bit hard to follow with the audio out of sync with the presentation
CONVERTING THE WHOLE CODE INTO .YAML , HOW TO DEBUG THAT .YAML THEN