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[ADVICE]Add a simple QuickStart Example #103

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IcyFeather233 opened this issue May 27, 2024 · 8 comments
Open

[ADVICE]Add a simple QuickStart Example #103

IcyFeather233 opened this issue May 27, 2024 · 8 comments
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good first issue Denotes an issue ready for a new contributor, according to the "help wanted" guidelines. kind/feature Categorizes issue or PR as related to a new feature.

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@IcyFeather233
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What should be added/modified:

The current QuickStart examples often require a variety of AI-related environments, but these environments may not be necessary during actual use. Moreover, the process of installing and configuring these environments is quite cumbersome. I believe that the project should have a simpler example to get started quickly, just like the MNIST handwritten digit recognition task in CNN.

@MooreZheng
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MooreZheng commented May 30, 2024

Good to hear that. One more example would be appreciated by the community.
Contribution guides to anyone who would be interested to tackle the issue: https://github.com/kubeedge/ianvs/blob/main/examples/how-to-contribute-examples.md

@AryanNanda17
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I would like to work on the issue. @MooreZheng @IcyFeather233 do you have any suggestion on what model example we can add in the quick-start guide?

@MooreZheng MooreZheng added the good first issue Denotes an issue ready for a new contributor, according to the "help wanted" guidelines. label Aug 13, 2024
@MooreZheng
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Welcome! As suggested via @IcyFeather233 , @AryanNanda17 might want to add MNIST with CNN, under single-task learning and try to write a new quick-start markdown as https://ianvs.readthedocs.io/en/latest/guides/quick-start.html

@MooreZheng MooreZheng added the kind/feature Categorizes issue or PR as related to a new feature. label Aug 13, 2024
@AryanNanda17
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Hello @MooreZheng

might want to add MNIST with CNN, under single-task learning and try to write a new quick-start markdown as https://ianvs.readthedocs.io/en/latest/guides/quick-start.html

Can we include this idea in LFX spring? I will be interested in contributing.

@AryanNanda17
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AryanNanda17 commented Jan 1, 2025

Maybe we can increase the scope of this idea, after the basic implementation of MNIST with CNN, under single-task learning is done.

@AryanNanda17
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Hi @MooreZheng and @hsj576,

I am deeply interested in contributing to the KubeEdge/Ianvs community and would love to participate in advancing the project further. If we could include this project in the LFX mentorship program, it would significantly boost my motivation to work with and for the community.

The CNCF community has already started accepting project proposals for the upcoming mentorship round. You can find more details here: CNCF Mentorship Program.

Would it be possible to pitch a proposal for this project? Or, do you have any other projects in mind that might align with the mentorship goals?

Looking forward to your guidance and support!

Thanks and regards,
Aryan Nanda

@MooreZheng
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Hi @MooreZheng and @hsj576,

I am deeply interested in contributing to the KubeEdge/Ianvs community and would love to participate in advancing the project further. If we could include this project in the LFX mentorship program, it would significantly boost my motivation to work with and for the community.

The CNCF community has already started accepting project proposals for the upcoming mentorship round. You can find more details here: CNCF Mentorship Program.

Would it be possible to pitch a proposal for this project? Or, do you have any other projects in mind that might align with the mentorship goals?

Looking forward to your guidance and support!

Thanks and regards, Aryan Nanda

Nice to hear from you Aryan. Good news is, on the KubeEdge routine meeting this Wednesday, KubeEdge has decided to join LFX 1st term 2025. We do seriously consider polishing ianvs during LFX and @FuryMartin also contributes critical ideas on proposals on the routine meeting of this week.

We start the drafting phase of all proposals in KubeEdge SIG AI today. Note that

  1. proposals have to be reviewed via KubeEdge maintainers and are not guaranteed to be accepted.
  2. After proposals settled, members are elected considering their previous performance to ensure the progress of new works, e.g., whether the previous project of a candidate was completed or not in KubeEdge.

@AryanNanda17
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Nice to hear from you Aryan. Good news is, on the KubeEdge routine meeting this Wednesday, KubeEdge has decided to join LFX 1st term 2025. We do seriously consider polishing ianvs during LFX and @FuryMartin also contributes critical ideas on proposals on the routine meeting of this week.

That is awesome! I look forward to the project proposals.

2. whether the previous project of a candidate was completed or not in KubeEdge.

@MooreZheng, what do you mean by previous projects of candidates in KubeEdge?

@FuryMartin also contributes critical ideas on proposals on the routine meeting of this week.

  • I was also looking forward to this week's meeting but there was no upcoming meeting schedule referencehere.

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